|
BACK TO INDEX Publications of year 2008 Books and proceedings
|
| Abstract: | In stepped-frequency radar, target motions produce range-profile distortions. Range shift, signal-to-noise ratio loss, and symmetric spreading are produced by target radial velocity, whereas target radial acceleration is mainly responsible for asymmetric smearing. Acceleration-distortion effects are usually negligible when a high Pulse Repetition Frequency (PRF) is used, although this is not the case for low-PRF radars. In this paper, a new motion-compensation technique based on contrast optimization is proposed. The innovative contributions of this paper are as follows: (1) A theoretical analysis of the distortions produced by target motions on the reconstruction of synthetic aperture radar is provided; (2) the proposed technique compensates both phase terms, which are due to target radial velocity and acceleration; therefore, synthetic range profiles can be focused by processing low-PRF radar returns; (3) a new cost function for the synthetic range profiles (namely, contrast) is defined and used for motion compensation; (4) the proposed technique can be applied to any kind of stepped-frequency waveforms; and (5) an estimation error analysis is performed, first theoretically and then by means of both simulations and real data. |
@ARTICLE{4637925,
author = {Berizzi, F. and Martorella, M. and Cacciamano, A. and Capria, A.},
title = {A Contrast-Based Algorithm For Synthetic Range-Profile Motion Compensation},
journal = {IEEE Transactions on Geoscience and Remote Sensing},
year = {2008},
volume = {46},
pages = {3053-3062},
number = {10},
month = {oct},
abstract = {In stepped-frequency radar, target motions produce range-profile distortions. Range shift, signal-to-noise ratio loss, and symmetric spreading are produced by target radial velocity, whereas target radial acceleration is mainly responsible for asymmetric smearing. Acceleration-distortion effects are usually negligible when a high Pulse Repetition Frequency (PRF) is used, although this is not the case for low-PRF radars. In this paper, a new motion-compensation technique based on contrast optimization is proposed. The innovative contributions of this paper are as follows: (1) A theoretical analysis of the distortions produced by target motions on the reconstruction of synthetic aperture radar is provided; (2) the proposed technique compensates both phase terms, which are due to target radial velocity and acceleration; therefore, synthetic range profiles can be focused by processing low-PRF radar returns; (3) a new cost function for the synthetic range profiles (namely, contrast) is defined and used for motion compensation; (4) the proposed technique can be applied to any kind of stepped-frequency waveforms; and (5) an estimation error analysis is performed, first theoretically and then by means of both simulations and real data.},
doi = {10.1109/TGRS.2008.2002576},
issn = {0196-2892},
keywords = {motion compensation, radar signal processing, synthetic aperture radarSAR image reconstruction, SNR loss, acceleration distortion effects, asymmetric smearing, contrast based algorithm, contrast optimization, estimation error analysis, low PRF radars, motion compensation technique, radar pulse repetition frequency, range shift, range-profile distortions, stepped frequency radar, stepped frequency waveform, symmetric spreading, synthetic aperture radar, synthetic range profile cost function, synthetic range-profile motion compensation, target motion, target radial acceleration, target radial velocity}
}
Keywords: SAR Processing, InSAR, Interferometry, SAR Interferometry, X-Band, Repeat-Pass Interferometry, Repeat-Pass, Single-Pass, Airborne SAR, PAMIR, Autofocus, Residual Motion Errors, Motion Compensation, MoComp, earthquakes, radar imaging, radar interferometry, remote sensing by radar, synthetic aperture radar, topography (Earth), Forschungsgesellschaft fur Angewandte Naturwissenschaften, Germany, PAMIR, Research Institute for High Frequency Physics and Radar Techniques, Wachtberg, X-band demonstrator, building recognition, building reconstruction, earthquake damage mapping, interferometric SAR sensor, phased array multifunctional imaging radar, radar imaging, radar-based urban analysis, remote-sensing applications, structural image analysis, subdecimeter resolution features, synthetic aperture radar, urban area monitoring, urban elevation models.
| Abstract: | In remote-sensing applications, the monitoring of urban areas by means of synthetic aperture radar (SAR) sensors has grown into a valuable and indispensable tool. Although SAR imaging with a spatial resolution down to 1 m is widespread, a resolution as fine as 10 cm and below is offered only by very few SAR sensors worldwide. In this paper, the potential of very high-resolution radar imaging of urban areas by means of SAR and interferometric imaging will be demonstrated and discussed. Results of urban SAR imaging down to subdecimeter resolution will be shown. Even though the immanent layover situation in urban areas is an obstacle to simple image understanding, a remedy can be found by using interferometric SAR imaging. Interferometric results based on very high-resolution SAR images acquired over urban areas, partially with a severe layover situation, will be presented. The corresponding data was acquired with the phased array multifunctional imaging radar (PAMIR), the X-band demonstrator of the Research Institute for High Frequency Physics and Radar Techniques (FHR), Forschungsgesellschaft fur Angewandte Naturwissenschaften (FGAN), Wachtberg, Germany. It can be stated that high-resolution interferometric SAR will be an important basis for upcoming radar-based urban analysis. |
@ARTICLE{brennerRoessing2008:InSARPAMIR,
author = {Brenner, Andreas .R. and Roessing, Ludwig},
title = {Radar Imaging of Urban Areas by Means of Very High-Resolution SAR and Interferometric SAR},
journal = {Geoscience and Remote Sensing, IEEE Transactions on},
year = {2008},
volume = {46},
pages = {2971-2982},
number = {10},
month = {Oct. },
abstract = {In remote-sensing applications, the monitoring of urban areas by means of synthetic aperture radar (SAR) sensors has grown into a valuable and indispensable tool. Although SAR imaging with a spatial resolution down to 1 m is widespread, a resolution as fine as 10 cm and below is offered only by very few SAR sensors worldwide. In this paper, the potential of very high-resolution radar imaging of urban areas by means of SAR and interferometric imaging will be demonstrated and discussed. Results of urban SAR imaging down to subdecimeter resolution will be shown. Even though the immanent layover situation in urban areas is an obstacle to simple image understanding, a remedy can be found by using interferometric SAR imaging. Interferometric results based on very high-resolution SAR images acquired over urban areas, partially with a severe layover situation, will be presented. The corresponding data was acquired with the phased array multifunctional imaging radar (PAMIR), the X-band demonstrator of the Research Institute for High Frequency Physics and Radar Techniques (FHR), Forschungsgesellschaft fur Angewandte Naturwissenschaften (FGAN), Wachtberg, Germany. It can be stated that high-resolution interferometric SAR will be an important basis for upcoming radar-based urban analysis.},
doi = {10.1109/TGRS.2008.920911},
issn = {0196-2892},
keywords = {SAR Processing, InSAR, Interferometry, SAR Interferometry, X-Band, Repeat-Pass Interferometry, Repeat-Pass, Single-Pass, Airborne SAR, PAMIR,
Autofocus, Residual Motion Errors, Motion Compensation, MoComp,earthquakes, radar imaging, radar interferometry, remote sensing by radar, synthetic aperture radar, topography (Earth), Forschungsgesellschaft fur Angewandte Naturwissenschaften, Germany, PAMIR, Research Institute for High Frequency Physics and Radar Techniques, Wachtberg, X-band demonstrator, building recognition, building reconstruction, earthquake damage mapping, interferometric SAR sensor, phased array multifunctional imaging radar, radar imaging, radar-based urban analysis, remote-sensing applications, structural image analysis, subdecimeter resolution features, synthetic aperture radar, urban area monitoring, urban elevation models},
owner = {ofrey},
pdf = {http://www.geo.uzh.ch/~ofrey/protected/PAPERS/brennerRoessing2008.pdf},
url = {http://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=4637926&isnumber=4637826}
}
Keywords: road traffic, synthetic aperture radar, target trackingGround Moving Target Indication mode, SAR-GMTI system, airborne radar sensor PAMIR, positioning accuracy, radial velocity, scan-MTI mode, signal-to-noise ratio, vehicles detection, wide area traffic monitoring experiment.
| Abstract: | This paper presents a wide area traffic monitoring experiment under real conditions, using the scan-MTI mode of the airborne radar sensor PAMIR. This flexible GMTI (Ground Moving Target Indication) mode was designed in order to rapidly monitor wide areas for moving targets. The scan operation enables the detection of targets from different aspect angles with a high revisit rate. The parameters (e.g., radial velocity, signal-to-noise ratio, and positioning accuracy) of the detected vehicles are investigated and compared to the expected theoretical GMTI performance. It will be shown that the scan-MTI mode is particularly adapted to perform an efficient wide-area traffic monitoring. |
@ARTICLE{4637928,
author = {Cerutti-Maori, D. and Klare, J. and Brenner, A.R. and Joachim H. G. Ender},
title = {Wide-Area Traffic Monitoring With the SAR/GMTI System PAMIR},
journal = {Geoscience and Remote Sensing, IEEE Transactions on},
year = {2008},
volume = {46},
pages = {3019-3030},
number = {10},
month = {Oct. },
abstract = {This paper presents a wide area traffic monitoring experiment under real conditions, using the scan-MTI mode of the airborne radar sensor PAMIR. This flexible GMTI (Ground Moving Target Indication) mode was designed in order to rapidly monitor wide areas for moving targets. The scan operation enables the detection of targets from different aspect angles with a high revisit rate. The parameters (e.g., radial velocity, signal-to-noise ratio, and positioning accuracy) of the detected vehicles are investigated and compared to the expected theoretical GMTI performance. It will be shown that the scan-MTI mode is particularly adapted to perform an efficient wide-area traffic monitoring.},
doi = {10.1109/TGRS.2008.923026},
issn = {0196-2892},
keywords = {road traffic, synthetic aperture radar, target trackingGround Moving Target Indication mode, SAR-GMTI system, airborne radar sensor PAMIR, positioning accuracy, radial velocity, scan-MTI mode, signal-to-noise ratio, vehicles detection, wide area traffic monitoring experiment}
}
Keywords: SAR Processing, Autofocus, Residual Motion Errors, WPCA, Weighted PCA, Weighted Phase Curvature Autofocus, Phase Curvature Autofocus, PCA, Phase Gradient Autofocus, PGA, Repeat-Pass Interferometry, Interferometry, InSAR, D-InSAR, Differential SAR Interferometry, E-SAR, airborne SAR, Baseline Calibration, Tomography, SAR Tomography, deformation, geophysical techniques, synthetic aperture radar, topography (Earth)E-SAR system, German Aerospace Center, airborne repeat-pass SAR Interferometry, autofocus algorithm, autofocus techniques, high-precision navigation system, image processing, interferometric-phase accuracy, phase curvature autofocus, residual motion errors, synthetic-aperture-radar, terrain deformations measurement, weighted least squares phase estimation.
| Abstract: | Airborne repeat-pass SAR systems are very sensible to subwavelength deviations from the reference track. To enable repeat-pass interferometry, a high-precision navigation system is needed. Due to the limit of accuracy of such systems, deviations in the order of centimeters remain between the real track and the processed one, causing mainly undesirable phase undulations and misregistration in the interferograms, referred to as residual motion errors. Up to now, only interferometric approaches, as multisquint, are used to compensate for such residual errors. In this paper, we present for the first time the use of the autofocus technique for residual motion errors in the repeat-pass interferometric context. A very robust autofocus technique has to be used to cope with the demands of the repeat-pass applications. We propose a new robust autofocus algorithm based on the weighted least squares phase estimation and the phase curvature autofocus (PCA) extended to the range-dependent case. We call this new algorithm weighted PCA. Different from multisquint, the autofocus approach has the advantage of being able to estimate motion deviations independently, leading to better focused data and correct impulse-response positioning. As a consequence, better coherence and interferometric-phase accuracy are achieved. Repeat-pass interferometry based only on image processing gains in robustness and reliability, since its performance does not deteriorate with time decorrelation and no assumptions need to be made on the interferometric phase. Repeat-pass data of the E-SAR system of the German Aerospace Center (DLR) are used to demonstrate the performance of the proposed approach. |
@ARTICLE{deMacedoScheiberMoreira2008:WPCA,
author = {C{\^a}mara de Macedo, Karlus A. and Scheiber, Rolf and Moreira, Alberto},
title = {{An Autofocus Approach for Residual Motion Errors With Application to Airborne Repeat-Pass SAR Interferometry}},
journal = {IEEE Transactions on Geoscience and Remote Sensing},
year = {2008},
volume = {46},
pages = {3151--3162},
number = {10},
month = {oct},
abstract = {Airborne repeat-pass SAR systems are very sensible to subwavelength deviations from the reference track. To enable repeat-pass interferometry, a high-precision navigation system is needed. Due to the limit of accuracy of such systems, deviations in the order of centimeters remain between the real track and the processed one, causing mainly undesirable phase undulations and misregistration in the interferograms, referred to as residual motion errors. Up to now, only interferometric approaches, as multisquint, are used to compensate for such residual errors. In this paper, we present for the first time the use of the autofocus technique for residual motion errors in the repeat-pass interferometric context. A very robust autofocus technique has to be used to cope with the demands of the repeat-pass applications. We propose a new robust autofocus algorithm based on the weighted least squares phase estimation and the phase curvature autofocus (PCA) extended to the range-dependent case. We call this new algorithm weighted PCA. Different from multisquint, the autofocus approach has the advantage of being able to estimate motion deviations independently, leading to better focused data and correct impulse-response positioning. As a consequence, better coherence and interferometric-phase accuracy are achieved. Repeat-pass interferometry based only on image processing gains in robustness and reliability, since its performance does not deteriorate with time decorrelation and no assumptions need to be made on the interferometric phase. Repeat-pass data of the E-SAR system of the German Aerospace Center (DLR) are used to demonstrate the performance of the proposed approach.},
doi = {10.1109/TGRS.2008.924004},
issn = {0196-2892},
keywords = {SAR Processing, Autofocus, Residual Motion Errors, WPCA, Weighted PCA, Weighted Phase Curvature Autofocus, Phase Curvature Autofocus, PCA, Phase Gradient Autofocus, PGA, Repeat-Pass Interferometry, Interferometry, InSAR, D-InSAR, Differential SAR Interferometry, E-SAR, airborne SAR, Baseline Calibration, Tomography, SAR Tomography, deformation, geophysical techniques, synthetic aperture radar, topography (Earth)E-SAR system, German Aerospace Center, airborne repeat-pass SAR Interferometry, autofocus algorithm, autofocus techniques, high-precision navigation system, image processing, interferometric-phase accuracy, phase curvature autofocus, residual motion errors, synthetic-aperture-radar, terrain deformations measurement, weighted least squares phase estimation},
owner = {ofrey},
pdf = {http://www.geo.uzh.ch/~ofrey/protected/PAPERS/deMacedoScheiberMoreira2008.pdf},
url = {http://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=4637939&isnumber=4637921}
}
Keywords: SAR Processing, SAR Tomography, Tomographic Processing, Multi-Baseline SAR, Time-Domain Back-Projection, Back-Projection, E-SAR, P-Band, Forestry.
| Abstract: | In recent years, various attempts have been undertaken to obtain information about the structure of forested areas from multi-baseline synthetic aperture radar data. Tomographic processing of such data has been demonstrated for airborne L-band data but the quality of the focused tomographic images is limited by several factors. In particular, the common Fourierbased focusing methods are susceptible to irregular and sparse sampling, two problems, that are unavoidable in case of multi-pass, multi-baseline SAR data acquired by an airborne system. In this paper, a tomographic focusing method based on the time-domain back-projection algorithm is proposed, which maintains the geometric relationship between the original sensor positions and the imaged target and is therefore able to cope with irregular sampling without introducing any approximations with respect to the geometry. The tomographic focusing quality is assessed by analysing the impulse response of simulated point targets and an in-scene corner reflector. And, in particular, several tomographic slices of a volume representing a forested area are given. The respective P-band tomographic data set consisting of eleven flight tracks has been acquired by the airborne E-SAR sensor of the German Aerospace Center (DLR). |
@ARTICLE{freyMorsdorfMeier08:SensorsTomo,
author = {Othmar Frey and Felix Morsdorf and Erich Meier},
title = {{Tomographic Imaging of a Forested Area By Airborne Multi-Baseline P-Band SAR}},
journal = {Sensors, Special Issue on Synthetic Aperture Radar},
year = {2008},
volume = {8},
pages = {5884--5896},
number = {9},
month = {sep},
abstract = {In recent years, various attempts have been undertaken to obtain information about the structure of forested areas from multi-baseline synthetic aperture radar data. Tomographic processing of such data has been demonstrated for airborne L-band data but the quality of the focused tomographic images is limited by several factors. In particular, the common Fourierbased focusing methods are susceptible to irregular and sparse sampling, two problems, that are unavoidable in case of multi-pass, multi-baseline SAR data acquired by an airborne system. In this paper, a tomographic focusing method based on the time-domain back-projection algorithm is proposed, which maintains the geometric relationship between the original sensor positions and the imaged target and is therefore able to cope with irregular sampling without introducing any approximations with respect to the geometry. The tomographic focusing quality is assessed by analysing the impulse response of simulated point targets and an in-scene corner reflector. And, in particular, several tomographic slices of a volume representing a forested area are given. The respective P-band tomographic data set consisting of eleven flight tracks has been acquired by the airborne E-SAR sensor of the German Aerospace Center (DLR).},
editor = {Daniele Riccio},
keywords = {SAR Processing, SAR Tomography, Tomographic Processing, Multi-Baseline SAR, Time-Domain Back-Projection, Back-Projection, E-SAR, P-Band, Forestry},
owner = {ofrey},
pdf = {http://www.geo.uzh.ch/~ofrey/myPublications/PAPERS/freyMorsdorfMeierSENSORS2008.pdf},
url = {http://www.mdpi.org/sensors/papers/s8095884.pdf}
}
Keywords: SAR Processing, Motion Compensation, MoComp, Airborne SAR, UAV, Unmanned Airborne Vehicle, LFM-CW, Continuous Wave SAR, Phase Gradient Autofocus, Autofocus, PGA, Range Alignment, Residual Motion Errors, mmW SAR, mmW, Ka-Band SAR.
| Abstract: | This paper presents an experimental Synthetic Aperture Radar (SAR) system that is under development in the Universidad Politécnica de Madrid. The system uses Linear Frequency Modulated Continuous Wave (LFM-CW) radar with a two antenna configuration for transmission and reception. The radar operates in the millimeter-wave band with a maximum transmitted bandwidth of 2 GHz. The proposed system is being developed for Unmanned Aerial Vehicle (UAV) operation. Motion errors in UAV operation can be critical. Therefore, this paper proposes a method for focusing SAR images with movement errors larger than the resolution cell. Typically, this problem is solved using two processing steps: first, coarse motion compensation based on the information provided by an Inertial Measuring Unit (IMU); and second, fine motion compensation for the residual errors within the resolution cell based on the received raw data. The proposed technique tries to focus the image without using data of an IMU. The method is based on a combination of the well known Phase Gradient Autofocus (PGA) for SAR imagery and typical algorithms for translational motion compensation on Inverse SAR (ISAR). This paper shows the first real experiments for obtaining high resolution SAR images using a car as a mobile platform for our radar. |
@ARTICLE{gonzalezPartidaAlmoroxGonzalezBurgosGarciaDortaNaranjo2008:UAVMoCo,
author = {Jos{\'e}-Tom{\'a}s Gonz{\'a}lez-Partida and Pablo Almorox-Gonz{\'a}lez and Mateo Burgos-Garc\'{\i}a and Blas-Pablo Dorta-Naranjo},
title = {SAR System for UAV Operation with Motion Error Compensation beyond the Resolution Cell},
journal = {Sensors, Special Issue on Synthetic Aperture Radar},
year = {2008},
volume = {8},
pages = {3384--3405},
number = {5},
abstract = {This paper presents an experimental Synthetic Aperture Radar (SAR) system that is under development in the Universidad Politécnica de Madrid. The system uses Linear Frequency Modulated Continuous Wave (LFM-CW) radar with a two antenna configuration for transmission and reception. The radar operates in the millimeter-wave band with a maximum transmitted bandwidth of 2 GHz. The proposed system is being developed for Unmanned Aerial Vehicle (UAV) operation. Motion errors in UAV operation can be critical. Therefore, this paper proposes a method for focusing SAR images with movement errors larger than the resolution cell. Typically, this problem is solved using two processing steps: first, coarse motion compensation based on the information provided by an Inertial Measuring Unit (IMU); and second, fine motion compensation for the residual errors within the resolution cell based on the received raw data. The proposed technique tries to focus the image without using data of an IMU. The method is based on a combination of the well known Phase Gradient Autofocus (PGA) for SAR imagery and typical algorithms for translational motion compensation on Inverse SAR (ISAR). This paper shows the first real experiments for obtaining high resolution SAR images using a car as a mobile platform for our radar.},
keywords = {SAR Processing, Motion Compensation, MoComp, Airborne SAR, UAV, Unmanned Airborne Vehicle, LFM-CW, Continuous Wave SAR, Phase Gradient Autofocus, Autofocus, PGA, Range Alignment, Residual Motion Errors, mmW SAR,mmW,Ka-Band SAR},
owner = {ofrey},
pdf = {http://www.geo.uzh.ch/~ofrey/protected/PAPERS/gonzalezPartidaAlmoroxGonzalezBurgosGarciaDortaNaranjo2008.pdf},
url = {http://www.mdpi.org/sensors/papers/s8053384.pdf}
}
Keywords: SAR Processing, Ionosphere, TEC, Total Electron Content, Troposphere, Path Delay.
@Article{jehlePerlerSmallSchubertMeier2008:EstimPathDelay,
AUTHOR = {Jehle, Michael and Perler, Donat and Small, David and Schubert, Adrian and Meier, Erich},
TITLE = {Estimation of Atmospheric Path Delays in {TerraSAR-X} Data using Models vs. Measurements},
JOURNAL = {Sensors},
VOLUME = {8},
YEAR = {2008},
NUMBER = {12},
PAGES = {8479-8491},
ISSN = {1424-8220},
DOI = {10.3390/s8128479},
keywords = {SAR Processing, Ionosphere, TEC, Total Electron Content, Troposphere, Path Delay},
}
Keywords: fast Fourier transforms, geophysical signal processing, radar imaging, radar signal processing, remote sensing by radar, synthetic aperture radar3D scene space ambiguity problem, AVME, RVME, SAR image shifting, SAR image space bases, absolute velocity measurement error, ambiguity region, bistatic SAR 2D PSF, bistatic SAR angular velocity direction, bistatic SAR image space, bistatic SAR signal processing, inverse fast Fourier transform, motion measurement error effects, perspective line, perspective operator, point spread function, range Doppler algorithm, relative velocity measurement error, scaled IFFT, space truncation error, synthetic aperture radar, time correlation radar signal processing, translational variant bistatic SAR imaging method.
| Abstract: | In this paper, we discuss the mapping between the 3-D scene space and the bistatic synthetic aperture radar (SAR) image space and show that when the direction of the angular velocity of the bistatic SAR remains constant, the process of bistatic SAR imaging can be approximately modeled as a perspective operator from the 3-D scene space to the 2-D image space, and the perspective line is perpendicular to the plane determined by the composition direction of the T/R line of sight and the composition direction of the angular velocity of the T/R platform. Then, we show that the 2-D point spread function of the bistatic SAR is determined not only by the range and ldquoazimuthrdquo resolutions but also by the geometry of the bistatic SAR and the bases of the SAR image space, and the concept ldquoambiguity regionrdquo is introduced to describe the ambiguity problem in the 3-D scene space. Then, the range-Doppler algorithm is discussed, and a new translational-variant bistatic SAR imaging method is proposed, which uses the scaled inverse fast Fourier transform (IFFT) technique to eliminate the translational-variant feature of the SAR space resolution. The space truncation error of this new algorithm is discussed to analyze the depth of focus of the scaled IFFT bistatic SAR imaging algorithms, and we find that the upper bounce of the space truncation error is proportional to the square of the distance from the scatterer to the T/R platforms. Last, the effects of motion measurement errors are discussed in detail, and, through theoretical analysis and numerical experiments, we show that the absolute position measurement error, the baseline measurement error, the perpendicular (vertical) component of the absolute velocity measurement error (AVME), and the perpendicular component of the relative velocity measurement error (RVME) cause SAR image shifting in the image space mainly, and the parallel component of the AVME and the parallel component of the RVME cause the SAR image to s- - everely defocus. |
@ARTICLE{junZhangYang2008:Bistatic,
author = {Shi Jun and Xiaoling Zhang and Jianyu Yang},
title = {Principle and Methods on Bistatic SAR Signal Processing via Time Correlation},
journal = {Geoscience and Remote Sensing, IEEE Transactions on},
year = {2008},
volume = {46},
pages = {3163-3178},
number = {10},
month = {Oct. },
abstract = {In this paper, we discuss the mapping between the 3-D scene space and the bistatic synthetic aperture radar (SAR) image space and show that when the direction of the angular velocity of the bistatic SAR remains constant, the process of bistatic SAR imaging can be approximately modeled as a perspective operator from the 3-D scene space to the 2-D image space, and the perspective line is perpendicular to the plane determined by the composition direction of the T/R line of sight and the composition direction of the angular velocity of the T/R platform. Then, we show that the 2-D point spread function of the bistatic SAR is determined not only by the range and ldquoazimuthrdquo resolutions but also by the geometry of the bistatic SAR and the bases of the SAR image space, and the concept ldquoambiguity regionrdquo is introduced to describe the ambiguity problem in the 3-D scene space. Then, the range-Doppler algorithm is discussed, and a new translational-variant bistatic SAR imaging method is proposed, which uses the scaled inverse fast Fourier transform (IFFT) technique to eliminate the translational-variant feature of the SAR space resolution. The space truncation error of this new algorithm is discussed to analyze the depth of focus of the scaled IFFT bistatic SAR imaging algorithms, and we find that the upper bounce of the space truncation error is proportional to the square of the distance from the scatterer to the T/R platforms. Last, the effects of motion measurement errors are discussed in detail, and, through theoretical analysis and numerical experiments, we show that the absolute position measurement error, the baseline measurement error, the perpendicular (vertical) component of the absolute velocity measurement error (AVME), and the perpendicular component of the relative velocity measurement error (RVME) cause SAR image shifting in the image space mainly, and the parallel component of the AVME and the parallel component of the RVME cause the SAR image to s- - everely defocus.},
doi = {10.1109/TGRS.2008.920369},
issn = {0196-2892},
keywords = {fast Fourier transforms, geophysical signal processing, radar imaging, radar signal processing, remote sensing by radar, synthetic aperture radar3D scene space ambiguity problem, AVME, RVME, SAR image shifting, SAR image space bases, absolute velocity measurement error, ambiguity region, bistatic SAR 2D PSF, bistatic SAR angular velocity direction, bistatic SAR image space, bistatic SAR signal processing, inverse fast Fourier transform, motion measurement error effects, perspective line, perspective operator, point spread function, range Doppler algorithm, relative velocity measurement error, scaled IFFT, space truncation error, synthetic aperture radar, time correlation radar signal processing, translational variant bistatic SAR imaging method}
}
Keywords: Monte Carlo methods, geophysical techniques, radar interferometry, radar polarimetry, remote sensing by radar, synthetic aperture radar, vegetationGerman Aerospace Research Center, JPL, Jet Propulsion Laboratory, L-band Advanced Land Observing Satellite, Monte Carlo simulation, airborne X-band polarimetric SAR, airborne interferometric SAR, alpha estimation, anisotropy estimation, bias removal algorithm, entropy estimation, forest, geophysical parameter estimation, grassland, multilook processing, phased array type L-band SAR, polarimetric SAR decomposition, scattering mechanisms, synthetic aperture radar, urban returns.
| Abstract: | Entropy, alpha, and anisotropy (H/alpha/A) of the polarimetric target decomposition have been an effective and popular tool for polarimetric synthetic aperture radar (SAR) image analysis and for a geophysical parameter estimation. However, multilook processing can severely affect the values of these parameters. In this paper, a Monte Carlo simulation is used to evaluate and remove the bias generated by the multilook effect on these parameters for various media composed of grassland, forest, and urban returns. Due to insufficient averaging, entropy is underestimated, and anisotropy is overestimated. We also found that the bias in the alpha angle can be either underestimated or overestimated depending on scattering mechanisms. Based on simulation results, efficient bias removal procedures have been developed. In particular, the entropy bias can be precisely corrected, and the amount of correction is independent of the radar frequency and SAR systems. Data from L-band Advanced Land Observing Satellite/phased array type L-band SAR, German Aerospace Research Center (DLR)/enhanced SAR, Jet Propulsion Laboratory (JPL)/airborne SAR, and X-band polarimetric and interferometric SAR are used for demonstration in this paper. |
@ARTICLE{4637955,
author = {Jong-Sen Lee and Ainsworth, T.L. and Kelly, J.P. and Lopez-Martinez, C.},
title = {Evaluation and Bias Removal of Multilook Effect on Entropy/Alpha/Anisotropy in Polarimetric SAR Decomposition},
journal = {Geoscience and Remote Sensing, IEEE Transactions on},
year = {2008},
volume = {46},
pages = {3039-3052},
number = {10},
month = {Oct. },
abstract = {Entropy, alpha, and anisotropy (H/alpha/A) of the polarimetric target decomposition have been an effective and popular tool for polarimetric synthetic aperture radar (SAR) image analysis and for a geophysical parameter estimation. However, multilook processing can severely affect the values of these parameters. In this paper, a Monte Carlo simulation is used to evaluate and remove the bias generated by the multilook effect on these parameters for various media composed of grassland, forest, and urban returns. Due to insufficient averaging, entropy is underestimated, and anisotropy is overestimated. We also found that the bias in the alpha angle can be either underestimated or overestimated depending on scattering mechanisms. Based on simulation results, efficient bias removal procedures have been developed. In particular, the entropy bias can be precisely corrected, and the amount of correction is independent of the radar frequency and SAR systems. Data from L-band Advanced Land Observing Satellite/phased array type L-band SAR, German Aerospace Research Center (DLR)/enhanced SAR, Jet Propulsion Laboratory (JPL)/airborne SAR, and X-band polarimetric and interferometric SAR are used for demonstration in this paper.},
doi = {10.1109/TGRS.2008.922033},
issn = {0196-2892},
keywords = {Monte Carlo methods, geophysical techniques, radar interferometry, radar polarimetry, remote sensing by radar, synthetic aperture radar, vegetationGerman Aerospace Research Center, JPL, Jet Propulsion Laboratory, L-band Advanced Land Observing Satellite, Monte Carlo simulation, airborne X-band polarimetric SAR, airborne interferometric SAR, alpha estimation, anisotropy estimation, bias removal algorithm, entropy estimation, forest, geophysical parameter estimation, grassland, multilook processing, phased array type L-band SAR, polarimetric SAR decomposition, scattering mechanisms, synthetic aperture radar, urban returns}
}
Keywords: SAR Processing, Ionosphere tomography, Spaceborne SAR, Electron density isolines, Inverse scattering technique for multi-layered random surfaces, Method of moment, MoM, TEC, Total Electron Content, CT, computerized tomography.
| Abstract: | Two models of ionosphere tomography based on spaceborne SAR (Synthetic Aperture Radar) are proposed. For HF-SAR the signal with sweeping frequency lower than the characteristic frequency of ionosphere will be scatted during the ionosphere propagation and completely reflected at a corresponding height. The ionospheric electron density isolines looked as series of random surfaces can be reconstructed from the HF-SAR echoes by using the inverse scattering technique for layered rough surfaces and the method of moment (MoM). The numerical simulation show that due to the MoM can provide a full wave solution, the ionosphere tomography with high resolution can be obtained as long as enough sampling data of HF-SAR echoes are used. For VHF/UHF/P/L-band SAR the TEC (Total Electron Content) can be obtained from the SAR echoes scattered by some strong point targets (such as the calibrators, etc.) appeared in the SAR imaged ground region, and the ionosphere tomography can be performed by CT technique. |
@ARTICLE{lili2008:IonoTomoSAR,
author = {Li, Lianlin and Li, Fang},
title = {Ionosphere tomography based on spaceborne SAR},
journal = {Advances in Space Research},
year = {2008},
volume = {42},
pages = {1187--1193},
number = {7},
month = {oct},
abstract = {Two models of ionosphere tomography based on spaceborne SAR (Synthetic Aperture Radar) are proposed. For HF-SAR the signal with sweeping frequency lower than the characteristic frequency of ionosphere will be scatted during the ionosphere propagation and completely reflected at a corresponding height. The ionospheric electron density isolines looked as series of random surfaces can be reconstructed from the HF-SAR echoes by using the inverse scattering technique for layered rough surfaces and the method of moment (MoM). The numerical simulation show that due to the MoM can provide a full wave solution, the ionosphere tomography with high resolution can be obtained as long as enough sampling data of HF-SAR echoes are used. For VHF/UHF/P/L-band SAR the TEC (Total Electron Content) can be obtained from the SAR echoes scattered by some strong point targets (such as the calibrators, etc.) appeared in the SAR imaged ground region, and the ionosphere tomography can be performed by CT technique.},
keywords = {SAR Processing, Ionosphere tomography, Spaceborne SAR, Electron density isolines, Inverse scattering technique for multi-layered random surfaces, Method of moment, MoM, TEC, Total Electron Content, CT, computerized tomography},
owner = {ofrey},
pdf = {http://www.geo.uzh.ch/~ofrey/protected/PAPERS/lili2008.pdf},
url = {http://www.sciencedirect.com/science/article/B6V3S-4R8H1XF-2/2/dd51165940e6c27023b473430dfddd6e}
}
Keywords: SAR Processing, Tomography, SAR Tomography, Multi-baseline SAR, Interpolation, Sector Interpolation, 3-D imaging, SAR Interferometry, Interferometry, InSAR, Spectral Analysis, Electromagnetic Tomography, Signal Sampling.
| Abstract: | Multibaseline (MB) synthetic aperture radar (SAR) tomography is a promising mode of SAR interferometry, allowing full 3-D imaging of volumetric and layover scatterers in place of a single elevation estimation capability for each SAR cell . However, Fourier-based MB SAR tomography is generally affected by unsatisfactory imaging quality due to a typically low number of baselines with irregular distribution. In this paper, we improve the basic elevation focusing technique by reconstructing a set of uniform baselines data exploiting in the interpolation step the ancillary information about the extension of a height sector which contains all the scatterers. This a priori information can be derived from the knowledge of the kind of the observed scenario (e.g., forest or urban). To demonstrate the concept, an imaging enhancement analysis is carried out by simulation. |
@ARTICLE{lombardiniPardini2008:Tomo,
author = {Lombardini, Fabrizio and Pardini, Matteo},
title = {{3-D SAR Tomography: The Multibaseline Sector Interpolation Approach}},
journal = {IEEE Geoscience and Remote Sensing Letters},
year = {2008},
volume = {5},
pages = {630-634},
number = {4},
month = {Oct. },
abstract = {Multibaseline (MB) synthetic aperture radar (SAR) tomography is a promising mode of SAR interferometry, allowing full 3-D imaging of volumetric and layover scatterers in place of a single elevation estimation capability for each SAR cell . However, Fourier-based MB SAR tomography is generally affected by unsatisfactory imaging quality due to a typically low number of baselines with irregular distribution. In this paper, we improve the basic elevation focusing technique by reconstructing a set of uniform baselines data exploiting in the interpolation step the ancillary information about the extension of a height sector which contains all the scatterers. This a priori information can be derived from the knowledge of the kind of the observed scenario (e.g., forest or urban). To demonstrate the concept, an imaging enhancement analysis is carried out by simulation.},
doi = {10.1109/LGRS.2008.2001283},
issn = {1545-598X},
keywords = {SAR Processing, Tomography, SAR Tomography, Multi-baseline SAR, Interpolation, Sector Interpolation, 3-D imaging, SAR Interferometry, Interferometry, InSAR, Spectral Analysis, Electromagnetic Tomography, Signal Sampling},
owner = {ofrey},
pdf = {http://www.geo.uzh.ch/~ofrey/protected/PAPERS/lombardiniPardini2008.pdf},
url = {http://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=4656455&isnumber=4656438}
}
Keywords: Faraday effect, electromagnetic wave polarisation, ionospheric disturbances, ionospheric electromagnetic wave propagation, ionospheric techniques, radar polarimetry, radiowave propagation, remote sensing by radar, spaceborne radar, synthetic aperture radarAdvanced Land Observing Satellite, Faraday rotation correction, Faraday rotation detection, Faraday rotation estimation, Faraday rotation prediction, PALSAR, SAR data quality degradation, data continuity, full polarimetric L-band SAR data, geophysical parameter recovery accuracy, kilometer scale ionospheric disturbances, spaceborne L-band SAR instrument, synthetic aperture radar.
| Abstract: | With the synthetic aperture radar (SAR) sensor PALSAR onboard the Advanced Land Observing Satellite, a new full-polarimetric spaceborne L-band SAR instrument has been launched into orbit. At L-band, Faraday rotation (FR) can reach significant values, degrading the quality of the received SAR data. One-way rotations exceeding 25 deg are likely to happen during the lifetime of PALSAR, which will significantly reduce the accuracy of geophysical parameter recovery if uncorrected. Therefore, the estimation and correction of FR effects is a prerequisite for data quality and continuity. In this paper, methods for estimating FR are presented and analyzed. The first unambiguous detection of FR in SAR data is presented. A set of real data examples indicates the quality and sensitivity of FR estimation from PALSAR data, allowing the measurement of FR with high precision in areas where such measurements were previously inaccessible. In examples, we present the detection of kilometer-scale ionospheric disturbances, a spatial scale that is not detectable by ground-based GPS measurements. An FR prediction method is presented and validated. Approaches to correct for the estimated FR effects are applied, and their effectiveness is tested on real data. |
@ARTICLE{meyerNicoll2008:FaradayRotation,
author = {Meyer, Franz J. and Nicoll, J.B.},
title = {Prediction, Detection, and Correction of Faraday Rotation in Full-Polarimetric L-Band SAR Data},
journal = {Geoscience and Remote Sensing, IEEE Transactions on},
year = {2008},
volume = {46},
pages = {3076-3086},
number = {10},
month = {Oct. },
abstract = {With the synthetic aperture radar (SAR) sensor PALSAR onboard the Advanced Land Observing Satellite, a new full-polarimetric spaceborne L-band SAR instrument has been launched into orbit. At L-band, Faraday rotation (FR) can reach significant values, degrading the quality of the received SAR data. One-way rotations exceeding 25 deg are likely to happen during the lifetime of PALSAR, which will significantly reduce the accuracy of geophysical parameter recovery if uncorrected. Therefore, the estimation and correction of FR effects is a prerequisite for data quality and continuity. In this paper, methods for estimating FR are presented and analyzed. The first unambiguous detection of FR in SAR data is presented. A set of real data examples indicates the quality and sensitivity of FR estimation from PALSAR data, allowing the measurement of FR with high precision in areas where such measurements were previously inaccessible. In examples, we present the detection of kilometer-scale ionospheric disturbances, a spatial scale that is not detectable by ground-based GPS measurements. An FR prediction method is presented and validated. Approaches to correct for the estimated FR effects are applied, and their effectiveness is tested on real data.},
doi = {10.1109/TGRS.2008.2003002},
issn = {0196-2892},
keywords = {Faraday effect, electromagnetic wave polarisation, ionospheric disturbances, ionospheric electromagnetic wave propagation, ionospheric techniques, radar polarimetry, radiowave propagation, remote sensing by radar, spaceborne radar, synthetic aperture radarAdvanced Land Observing Satellite, Faraday rotation correction, Faraday rotation detection, Faraday rotation estimation, Faraday rotation prediction, PALSAR, SAR data quality degradation, data continuity, full polarimetric L-band SAR data, geophysical parameter recovery accuracy, kilometer scale ionospheric disturbances, spaceborne L-band SAR instrument, synthetic aperture radar}
}
Keywords: SAR Processing, SAR Tomography, geophysical techniques, geophysics computing, image processing, radar interferometry, remote sensing by radar, synthetic aperture radar, topography (Earth)ENVISAT images, Monte Carlo simulations, SAR interferometry applications, decorrelation models, interferometric phases, line-of-sight displacement, line-of-sight motion, multiimage synthetic aperture radar interferometry, physical parameters, residual topography, target statistics.
| Abstract: | This paper focuses on multiimage synthetic aperture radar interferometry (InSAR) in the presence of distributed scatterers, paying particular attention to the role of target decorrelation in the estimation process. This phenomenon is accounted for by splitting the analysis into two steps. In the first step, we estimate the interferometric phases from the data, whereas in the second step, we use these phases to retrieve the physical parameters of interest, such as line-of-sight (LOS) displacement and residual topography. In both steps, we make the hypothesis that target statistics are at least approximately known. This approach is suited both to derive the performances of InSAR with different decorrelation models and for providing an actual estimate of LOS motion and topography. Results achieved from Monte Carlo simulations and a set of repeated pass ENVISAT images are shown. |
@ARTICLE{montiGuarnieriTebaldiniTGRS2008:TomoInSAR,
author = {Monti-Guarnieri, Andrea and Tebaldini, Stefano},
title = {On the Exploitation of Target Statistics for SAR Interferometry Applications},
journal = {IEEE Transactions on Geoscience and Remote Sensing},
year = {2008},
volume = {46},
pages = {3436-3443},
number = {11},
month = {nov},
abstract = {This paper focuses on multiimage synthetic aperture radar interferometry (InSAR) in the presence of distributed scatterers, paying particular attention to the role of target decorrelation in the estimation process. This phenomenon is accounted for by splitting the analysis into two steps. In the first step, we estimate the interferometric phases from the data, whereas in the second step, we use these phases to retrieve the physical parameters of interest, such as line-of-sight (LOS) displacement and residual topography. In both steps, we make the hypothesis that target statistics are at least approximately known. This approach is suited both to derive the performances of InSAR with different decorrelation models and for providing an actual estimate of LOS motion and topography. Results achieved from Monte Carlo simulations and a set of repeated pass ENVISAT images are shown.},
doi = {10.1109/TGRS.2008.2001756},
issn = {0196-2892},
keywords = {SAR Processing, SAR Tomography, geophysical techniques, geophysics computing, image processing, radar interferometry, remote sensing by radar, synthetic aperture radar, topography (Earth)ENVISAT images, Monte Carlo simulations, SAR interferometry applications, decorrelation models, interferometric phases, line-of-sight displacement, line-of-sight motion, multiimage synthetic aperture radar interferometry, physical parameters, residual topography, target statistics},
owner = {ofrey},
pdf = {http://www.geo.uzh.ch/~ofrey/protected/PAPERS/montiGuarnieriTebaldiniTGRS2008.pdf},
url = {http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=4685949&isnumber=4685926}
}
Keywords: SAR Processing, SAR Tomography, Tomography, Residual Motion Errors, InSAR, SAR Interferometry, Interferometry, antenna arrays, direction-of-arrival estimation, DOA estimation, hybrid Cramer-Rao bound, multibaseline interferometers, randomly perturbed arrays, remote sensing systems, signal direction of arrival, synthetic aperture radar.
| Abstract: | In this correspondence we derive explicit expressions for the hybrid Cramer-Rao lower bound (HCRB) on the estimation accuracy of signal direction of arrival (DOA) from data collected by randomly perturbed arrays. The presence of a wavefront spatial decorrelation, which is modeled as a multiplicative correlated noise, has also been taken into account in the data model, since it is typical in those applications involving extended sources. In particular, we consider perturbations in sensor positions. Existing approaches to DOA HCRB calculation do not consider the presence of multiplicative noise and are referred to the assumption of small perturbations only, still not being worked out explicitly. Here, we assume that the impinging wavefronts are coming from broadside or more generally from a narrow DOA sector, allowing the explicit derivation of the HCRB for any variance of the sensor positioning errors in the line-of-sight direction. This scenario corresponds to the typical operative condition of remote sensing systems such as synthetic aperture radar (SAR) multibaseline interferometers, for which a few HCRB sample curves are reported. |
@ARTICLE{pardiniLombardiniGini2008:Tomo,
author = {Pardini, Matteo and Lombardini, Fabrizio and Gini, Fabrizio},
title = {{The Hybrid Cram{\'e}r -- Rao Bound on Broadside DOA Estimation of Extended Sources in Presence of Array Errors}},
journal = {IEEE Transactions on Signal Processing},
year = {2008},
volume = {56},
pages = {1726-1730},
number = {4},
month = {apr},
abstract = {In this correspondence we derive explicit expressions for the hybrid Cramer-Rao lower bound (HCRB) on the estimation accuracy of signal direction of arrival (DOA) from data collected by randomly perturbed arrays. The presence of a wavefront spatial decorrelation, which is modeled as a multiplicative correlated noise, has also been taken into account in the data model, since it is typical in those applications involving extended sources. In particular, we consider perturbations in sensor positions. Existing approaches to DOA HCRB calculation do not consider the presence of multiplicative noise and are referred to the assumption of small perturbations only, still not being worked out explicitly. Here, we assume that the impinging wavefronts are coming from broadside or more generally from a narrow DOA sector, allowing the explicit derivation of the HCRB for any variance of the sensor positioning errors in the line-of-sight direction. This scenario corresponds to the typical operative condition of remote sensing systems such as synthetic aperture radar (SAR) multibaseline interferometers, for which a few HCRB sample curves are reported.},
doi = {10.1109/TSP.2007.910540},
issn = {1053-587X},
keywords = {SAR Processing, SAR Tomography, Tomography, Residual Motion Errors, InSAR, SAR Interferometry, Interferometry, antenna arrays, direction-of-arrival estimation, DOA estimation, hybrid Cramer-Rao bound, multibaseline interferometers, randomly perturbed arrays, remote sensing systems, signal direction of arrival, synthetic aperture radar},
owner = {ofrey},
pdf = {http://www.geo.uzh.ch/~ofrey/protected/PAPERS/pardiniLombardiniGini2008.pdf},
url = {http://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=4471888&isnumber=4471869}
}
Keywords: SAR Processing, BFNT, Backward-Forward to the Nominale Track, Airborne SAR, D-InSAR, differential SAR interferometry, Interferometry, OrbiSAR, X-Band, Motion Compensation, Residual Motion Errors, Autofocus, Airborne SAR, airborne radar, motion compensation, radar imaging, synthetic aperture radar airborne SAR images, digital elevation model inaccuracies, motion compensation errors, phase errors.
| Abstract: | Differential synthetic aperture radar interferometry (DInSAR) is a remote sensing technique that allows monitoring ground deformation with accuracy of the order of fractions of the radiated wavelength, by means of proper combination and processing of repeat-pass data. In contrast to the satellite case, application of such a technique to airborne data is not, today, a well-established task. Several airborne campaigns, involving mainly C/L-band data, have been planned in the last years to exploit the potentialities of these more flexible platforms for deformation monitoring. In this paper, we show the results of an airborne DInSAR X-band experiment carried out over the Perugia area (center of Italy) by using the OrbiSAR system. We discuss the processing chain applied to the acquired data, which allows achieving a satisfactory compromise between accuracy and efficiency. Eleven repeated passes were carried out in two days; two corner reflectors were located on the ground in a hilly region. One corner reflector was vertically moved between the two days to evaluate the system detection capability. Moreover, we carry out an analysis of all possible differential interferograms for a region 2 x 4 km wide. |
@ARTICLE{pernaWimmerMoreiraFornaro2008:DInSAR,
author = {Perna, S. and Wimmer, C. and Moreira, J. and Fornaro, G.},
title = {X-Band Airborne Differential Interferometry: Results of the OrbiSAR Campaign Over the Perugia Area},
journal = {Geoscience and Remote Sensing, IEEE Transactions on},
year = {2008},
volume = {46},
pages = {489-503},
number = {2},
month = feb,
abstract = {Differential synthetic aperture radar interferometry (DInSAR) is a remote sensing technique that allows monitoring ground deformation with accuracy of the order of fractions of the radiated wavelength, by means of proper combination and processing of repeat-pass data. In contrast to the satellite case, application of such a technique to airborne data is not, today, a well-established task. Several airborne campaigns, involving mainly C/L-band data, have been planned in the last years to exploit the potentialities of these more flexible platforms for deformation monitoring. In this paper, we show the results of an airborne DInSAR X-band experiment carried out over the Perugia area (center of Italy) by using the OrbiSAR system. We discuss the processing chain applied to the acquired data, which allows achieving a satisfactory compromise between accuracy and efficiency. Eleven repeated passes were carried out in two days; two corner reflectors were located on the ground in a hilly region. One corner reflector was vertically moved between the two days to evaluate the system detection capability. Moreover, we carry out an analysis of all possible differential interferograms for a region 2 x 4 km wide.},
issn = {0196-2892},
keywords = {SAR Processing, BFNT, Backward-Forward to the Nominale Track, Airborne SAR, D-InSAR, differential SAR interferometry, Interferometry, OrbiSAR, X-Band, Motion Compensation, Residual Motion Errors, Autofocus, Airborne SAR, airborne radar, motion compensation, radar imaging, synthetic aperture radar airborne SAR images, digital elevation model inaccuracies, motion compensation errors, phase errors},
pdf = {http://www.geo.uzh.ch/~ofrey/protected/PAPERS/pernaWimmerMoreiraFornaro2008.pdf},
url = {http://www.ieeexplore.ieee.org/iel5/36/4432701/04432715.pdf}
}
Keywords: SAR Processing, DInSAR, InSAR, Interferometry, digital elevation models, error analysis, motion compensation, MoComp, radar interferometry, Multi-Baseline SAR, synthetic aperture radar, topography (Earth)DLR, Experimental SAR system, E-SAR, Airborne SAR, German Aerospace Center, agricultural fields, airborne differential synthetic aperture radar interferometry, baseline error, corner reflector, deformation, differential interferometry processor, digital elevation model, image coregistration, residual motion errors, temporal evolution, topography.
| Abstract: | This paper presents airborne differential synthetic aperture radar (SAR) interferometry results using a stack of 14 images, which were acquired by the Experimental SAR system of the German Aerospace Center (DLR) during a time span of 2.5 h. An advanced differential technique is used to retrieve the error in the digital elevation model and the temporal evolution of the deformation for every coherent pixel in the image. The two main limitations in airborne SAR processing are analyzed, namely, the existence of residual motion errors (RMEs) (inaccuracies in the navigation system on the order of 1-5 cm) and the accommodation of the topography and the aperture dependence on motion errors during the processing. The coupling between them is also addressed, showing that the estimation of the differential RME, i.e., baseline error, can be biased when using techniques based on the coregistration between interferometric looks. The SAR focusing chain to process the data is also presented together with the modifications in the differential interferometry processor to deal with the remaining baseline error. The detected motion of a corner reflector and the measured deformation in several agricultural fields allows one to validate the proposed techniques. |
@ARTICLE{pratsReigberMallorquiScheiberMoreira2008:DInSAR,
author = {Prats, Pau and Mallorqui, J.J. and Reigber, Andreas and Scheiber, Rolf and Moreira, Alberto},
title = {{Estimation of the Temporal Evolution of the Deformation Using Airborne Differential SAR Interferometry}},
journal = {IEEE Transactions on Geoscience and Remote Sensing},
year = {2008},
volume = {46},
pages = {1065-1078},
number = {4},
month = {apr},
abstract = {This paper presents airborne differential synthetic aperture radar (SAR) interferometry results using a stack of 14 images, which were acquired by the Experimental SAR system of the German Aerospace Center (DLR) during a time span of 2.5 h. An advanced differential technique is used to retrieve the error in the digital elevation model and the temporal evolution of the deformation for every coherent pixel in the image. The two main limitations in airborne SAR processing are analyzed, namely, the existence of residual motion errors (RMEs) (inaccuracies in the navigation system on the order of 1-5 cm) and the accommodation of the topography and the aperture dependence on motion errors during the processing. The coupling between them is also addressed, showing that the estimation of the differential RME, i.e., baseline error, can be biased when using techniques based on the coregistration between interferometric looks. The SAR focusing chain to process the data is also presented together with the modifications in the differential interferometry processor to deal with the remaining baseline error. The detected motion of a corner reflector and the measured deformation in several agricultural fields allows one to validate the proposed techniques.},
issn = {0196-2892},
keywords = {SAR Processing, DInSAR, InSAR, Interferometry, digital elevation models, error analysis, motion compensation, MoComp, radar interferometry, Multi-Baseline SAR, synthetic aperture radar, topography (Earth)DLR, Experimental SAR system, E-SAR, Airborne SAR, German Aerospace Center, agricultural fields, airborne differential synthetic aperture radar interferometry, baseline error, corner reflector, deformation, differential interferometry processor, digital elevation model, image coregistration, residual motion errors, temporal evolution, topography},
owner = {ofrey},
pdf = {http://www.geo.uzh.ch/~ofrey/protected/PAPERS/pratsReigberMallorquiScheiberMoreira2008.pdf},
url = {http://ieeexplore.ieee.org/iel5/36/4475343/04464121.pdf}
}
Keywords: geophysical techniques, synthetic aperture radarBiSAR imaging problem, NLCS algorithm, azimuth perturbation, compensation methods, differential range cell migration correction, local fit method, nonlinear chirp scaling algorithm, one-stationary bistatic SAR, range chirp scaling function.
| Abstract: | This paper deals with the imaging problem of one-stationary bistatic SAR (BiSAR) with large bistatic angle. An improved nonlinear chirp scaling (NLCS) algorithm is proposed for this BiSAR. The main work here includes three aspects. First, a range chirp scaling function for correcting the differential range cell migration correction is derived. Then, the azimuth perturbation is generated by local fit method, which makes the NLCS algorithm suitable for the large bistatic angle case. Furthermore, the negative effects introduced by the perturbation (including phase error and locality error) are discussed, and some compensation methods are proposed to enhance the capability of the algorithm. The simulating results exhibited at the end of this paper validate the correctness of the analysis and the feasibility of the algorithm. |
@ARTICLE{QiuHuDing2008:NLCS,
author = {Xiaolan Qiu and Donghui Hu and Chibiao Ding},
title = {An Improved NLCS Algorithm With Capability Analysis for One-Stationary BiSAR},
journal = {Geoscience and Remote Sensing, IEEE Transactions on},
year = {2008},
volume = {46},
pages = {3179-3186},
number = {10},
month = {Oct. },
abstract = {This paper deals with the imaging problem of one-stationary bistatic SAR (BiSAR) with large bistatic angle. An improved nonlinear chirp scaling (NLCS) algorithm is proposed for this BiSAR. The main work here includes three aspects. First, a range chirp scaling function for correcting the differential range cell migration correction is derived. Then, the azimuth perturbation is generated by local fit method, which makes the NLCS algorithm suitable for the large bistatic angle case. Furthermore, the negative effects introduced by the perturbation (including phase error and locality error) are discussed, and some compensation methods are proposed to enhance the capability of the algorithm. The simulating results exhibited at the end of this paper validate the correctness of the analysis and the feasibility of the algorithm.},
doi = {10.1109/TGRS.2008.921569},
issn = {0196-2892},
keywords = {geophysical techniques, synthetic aperture radarBiSAR imaging problem, NLCS algorithm, azimuth perturbation, compensation methods, differential range cell migration correction, local fit method, nonlinear chirp scaling algorithm, one-stationary bistatic SAR, range chirp scaling function}
}
Keywords: SAR Processing, Time-Domain Back-Projection, Backprojection, Back-Projection, Fast Factorized Back-Projection, Comparison of Algorithms, interpolation, radar imaging, synthetic aperture radar, time-domain analysis, ultra wideband radar, UWB SAR, interpolation method, phase error, polar version, subimage version, time domain SAR algorithm, Factorized Backprojection.
| Abstract: | This paper presents a comparative study of the polar and the subimage based variants of the time domain SAR algorithm Fast Factorized Backprojection. The difference between the two variants with regard to the phase error, which causes defocusing in the image, is investigated. The difference between the algorithms in interpolation between stages is also discussed. To investigate the sidelobes in azimuth, the paper gives simulation results for a low frequency UWB SAR system for both algorithms. How the algorithms differ with regard to amount of beams and length of beams is also discussed. |
@ARTICLE{sjoerenVuPetterson2008:FFBPComparison,
author = {Sjogren, T.K. and Vu, V.T. and Pettersson, M.I.},
title = {{A comparative study of the polar version with the subimage version of Fast Factorized Backprojection in UWB SAR}},
journal = {International Radar Symposium},
year = {2008},
pages = {1-4},
month = {May},
abstract = {This paper presents a comparative study of the polar and the subimage based variants of the time domain SAR algorithm Fast Factorized Backprojection. The difference between the two variants with regard to the phase error, which causes defocusing in the image, is investigated. The difference between the algorithms in interpolation between stages is also discussed. To investigate the sidelobes in azimuth, the paper gives simulation results for a low frequency UWB SAR system for both algorithms. How the algorithms differ with regard to amount of beams and length of beams is also discussed.},
doi = {10.1109/IRS.2008.4585740},
keywords = {SAR Processing, Time-Domain Back-Projection, Backprojection, Back-Projection, Fast Factorized Back-Projection, Comparison of Algorithms, interpolation, radar imaging, synthetic aperture radar, time-domain analysis, ultra wideband radar, UWB SAR, interpolation method, phase error, polar version, subimage version, time domain SAR algorithm,Factorized Backprojection},
owner = {ofrey},
pdf = {http://www.geo.uzh.ch/~ofrey/protected/PAPERS/sjoerenVuPetterson2008.pdf},
url = {http://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=4585740&isnumber=4585695}
}
Keywords: SAR Processing, Bistatic SAR, Loffeld bistatic formula, airborne configuration, azimuth time-bandwidth products, bistatic point target reference spectrum, bistatic synthetic aperture radar, general bistatic SAR processing, spaceborne configuration, total azimuth modulation, total azimuth phase, geophysical signal processing, radar signal processing, synthetic aperture radar;.
| Abstract: | A bistatic point target reference spectrum (BPTRS) based on Loffeld's bistatic formula (LBF) is derived in this letter. For LBF, the same contributions of the transmitter and receiver to the total azimuth modulation are assumed. This assumption results in the failure of LBF in the extreme configuration (i.e., spaceborne/airborne configuration). For general bistatic configurations, the azimuth modulations are unequal for the transmitter and receiver due to the different slant ranges and velocities. Therefore, the azimuth time-bandwidth products (TBPs) from the transmitter and receiver are different; in some cases (e.g., spaceborne/airborne case), one of them might be very small, which might even result in a serious error of the principle of stationary phase. This letter uses TBP to weight the azimuth phase modulation contributions of the transmitter and receiver to the common azimuth spectrum to approximately obtain the point of stationary phase of the total azimuth phase history. Simulations show that the proposed BPTRS can work well for spaceborne/airborne configurations. |
@ARTICLE{WangLoffeldUlAnnNiesOrtizSamarah2008:Bistatic,
author={Wang, Robert and Loffeld, Otmar and Ul-Ann, Qurat and Nies, Holger and Ortiz, Amaya Medrano and Samarah, Ashraf},
journal=IEEE_J_GRSL,
title={A Bistatic Point Target Reference Spectrum for General Bistatic {SAR} Processing},
year={2008},
month=jul,
volume={5},
number={3},
pages={517-521},
abstract={ A bistatic point target reference spectrum (BPTRS) based on Loffeld's bistatic formula (LBF) is derived in this letter. For LBF, the same contributions of the transmitter and receiver to the total azimuth modulation are assumed. This assumption results in the failure of LBF in the extreme configuration (i.e., spaceborne/airborne configuration). For general bistatic configurations, the azimuth modulations are unequal for the transmitter and receiver due to the different slant ranges and velocities. Therefore, the azimuth time-bandwidth products (TBPs) from the transmitter and receiver are different; in some cases (e.g., spaceborne/airborne case), one of them might be very small, which might even result in a serious error of the principle of stationary phase. This letter uses TBP to weight the azimuth phase modulation contributions of the transmitter and receiver to the common azimuth spectrum to approximately obtain the point of stationary phase of the total azimuth phase history. Simulations show that the proposed BPTRS can work well for spaceborne/airborne configurations. },
keywords={SAR Processing,Bistatic SAR,Loffeld bistatic formula;airborne configuration;azimuth time-bandwidth products;bistatic point target reference spectrum;bistatic synthetic aperture radar;general bistatic SAR processing;spaceborne configuration;total azimuth modulation;total azimuth phase;geophysical signal processing;radar signal processing;synthetic aperture radar;},
doi={10.1109/LGRS.2008.923542},
ISSN={1545-598X},
}
Keywords: SAR Processing, LFM-CW, LFM-CW SAR, MoComp, motion compensation, CSA, ECS, Chirp Scaling, Extended Chirp Scaling, FSA, Frequency Scaling Algorithm, Range-Doppler Algorithm, synthetic aperture radar, Brigham Young University, muSAR system, LFM-CW signal model, SAR image quality, aircraft, atmospheric turbulence, high-resolution synthetic aperture radar systems, linear frequency-modulated continuous-wave signal, motion compensation, motion correction algorithms, unmanned aerial vehicle, Airborne SAR, geophysical techniques,.
| Abstract: | Small low-cost high-resolution synthetic aperture radar (SAR) systems are made possible by using a linear frequency-modulated continuous-wave (LFM-CW) signal. SAR processing assumes that the sensor is moving in a straight line at a constant speed, but in actuality, an unmanned aerial vehicle (UAV) or airplane will often significantly deviate from this ideal. This nonideal motion can seriously degrade the SAR image quality. In a continuous-wave system, this motion happens during the radar pulse, which means that existing motion compensation techniques that approximate the position as constant over a pulse are limited for LFM-CW SAR. Small aircraft and UAVs are particularly susceptible to atmospheric turbulence, making the need for motion compensation even greater for SARs operating on these platforms. In this paper, the LFM-CW SAR signal model is presented, and processing algorithms are discussed. The effects of nonideal motion on the SAR signal are derived, and new methods for motion correction are developed, which correct for motion during the pulse. These new motion correction algorithms are verified with simulated data and with actual data collected using the Brigham Young University muSAR system. |
@ARTICLE{zauggLongTGRS2008:MocompLFMCWSAR,
author = {Zaugg, Evan C. and Long, David G.},
title = {{Theory and Application of Motion Compensation for LFM-CW SAR}},
journal = {IEEE Transactions on Geoscience and Remote Sensing},
year = {2008},
volume = {46},
pages = {2990-2998},
number = {10},
month = {Oct. },
abstract = {Small low-cost high-resolution synthetic aperture radar (SAR) systems are made possible by using a linear frequency-modulated continuous-wave (LFM-CW) signal. SAR processing assumes that the sensor is moving in a straight line at a constant speed, but in actuality, an unmanned aerial vehicle (UAV) or airplane will often significantly deviate from this ideal. This nonideal motion can seriously degrade the SAR image quality. In a continuous-wave system, this motion happens during the radar pulse, which means that existing motion compensation techniques that approximate the position as constant over a pulse are limited for LFM-CW SAR. Small aircraft and UAVs are particularly susceptible to atmospheric turbulence, making the need for motion compensation even greater for SARs operating on these platforms. In this paper, the LFM-CW SAR signal model is presented, and processing algorithms are discussed. The effects of nonideal motion on the SAR signal are derived, and new methods for motion correction are developed, which correct for motion during the pulse. These new motion correction algorithms are verified with simulated data and with actual data collected using the Brigham Young University muSAR system.},
doi = {10.1109/TGRS.2008.921958},
issn = {0196-2892},
keywords = {SAR Processing, LFM-CW, LFM-CW SAR, MoComp, motion compensation, CSA, ECS, Chirp Scaling, Extended Chirp Scaling, FSA, Frequency Scaling Algorithm, Range-Doppler Algorithm, synthetic aperture radar, Brigham Young University, muSAR system, LFM-CW signal model, SAR image quality, aircraft, atmospheric turbulence, high-resolution synthetic aperture radar systems, linear frequency-modulated continuous-wave signal, motion compensation, motion correction algorithms, unmanned aerial vehicle, Airborne SAR, geophysical techniques,},
pdf = {http://www.geo.uzh.ch/~ofrey/protected/PAPERS/zauggLongTGRS2008.pdf},
url = {http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=4637982&isnumber=4637826}
}
Conference articles
-
Marcelo Albuquerque,
Pau Prats,
and Rolf Scheiber.
Applications of Time-Domain Back-Projection SAR Processing in the Airborne Case.
In European Conference on Synthetic Aperture Radar (EUSAR),
pages 4,
06 2008.
VDE Verlag GmbH.
Keywords: SAR Processsing, Time-Domain Back-Projection, TDBP, Back-Projection, Synthetic Aperture Radar (SAR), motion compensation, tomography, Airborne SAR, E-SAR, Topography-dependent motion compensation, Motion Compensation, MoComp, Interferometry, Non-Linear SAR, Non-Linear Flight Tracks.Abstract: The Back-Projection Algorithm is a SAR processing approach that uses time-domain convolution of the SAR data in order to perform SAR focusing. Some benefits of this approach are exact inversion, ideal motion compensation including topography information and handling of general aperture geometries. The implementation of the Back-Projection Algorithm was done focusing on the parallelization aspects. Applications of the algorithm are presented with respect to topography adaptive processing, direct generation of map projections and consideration of non linear trajectories. @INPROCEEDINGS{albuquerquePratsScheiberEUSAR08:TDBP, author = {Albuquerque, Marcelo and Prats, Pau and Scheiber, Rolf}, title = {Applications of Time-Domain Back-Projection SAR Processing in the Airborne Case}, booktitle = {European Conference on Synthetic Aperture Radar (EUSAR)}, year = {2008}, pages = {4}, month = {06}, publisher = {VDE Verlag GmbH}, abstract = {The Back-Projection Algorithm is a SAR processing approach that uses time-domain convolution of the SAR data in order to perform SAR focusing. Some benefits of this approach are exact inversion, ideal motion compensation including topography information and handling of general aperture geometries. The implementation of the Back-Projection Algorithm was done focusing on the parallelization aspects. Applications of the algorithm are presented with respect to topography adaptive processing, direct generation of map projections and consideration of non linear trajectories.}, isbn = {978-3-8007-3084-1}, journal = {Proceedings of the European Conference on Synthetic Aperture Radar (EUSAR)}, keywords = {SAR Processsing, Time-Domain Back-Projection, TDBP, Back-Projection, Synthetic Aperture Radar (SAR), motion compensation, tomography, Airborne SAR, E-SAR,Topography-dependent motion compensation, Motion Compensation, MoComp, Interferometry, Non-Linear SAR, Non-Linear Flight Tracks}, location = {Friedrichshafen, Germany}, owner = {ofrey}, pdf = {http://www.geo.uzh.ch/~ofrey/protected/PAPERS/albuquerquePratsScheiberEUSAR08.pdf}, url = {http://elib.dlr.de/53756/01/albuquerque_EUSAR2008_time_domain.pdf} } -
Michael Brandfass and Luis Fernando Lobianco.
Modified Fast Factorized Backprojection as Applied to X-Band Data for Curved Flight Paths.
In European Conference on Synthetic Aperture Radar (EUSAR),
pages 4,
June 2008.
VDE Verlag GmbH.
Keywords: SAR Processsing, Time-Domain Back-Projection, TDBP, Back-Projection, Fast Factorized Back-Projection, FFBP, Fast Back-Projection, Synthetic Aperture Radar (SAR), motion compensation, tomography, Airborne SAR, X-Band, Motion Compensation, MoComp, Non-Linear SAR, Non-Linear Flight Tracks.Abstract: A Fast Factorized Backprojection scheme modified to X-band frequencies and applicable to small aperture beamwidths is presented to compute SAR images from real and synthetic airborne data sets. The numerical complexity and memory consumption of the algorithm is verified and compared to ordinary Backprojection. The modified Fast Factorized Backprojection scheme is investigated for exceedingly curved flight paths and compared to an \u03c9-k algorithm in combination with a motion error correction. Excellent SAR image focusing results were found for the modified Fast Factorized Backprojection approach while keeping the numerical complexity to O(N2log(N)). @INPROCEEDINGS{brandfassLobiancoEUSAR2008:FFBPforXBand, author = {Brandfass, Michael and Lobianco, Luis Fernando}, title = {Modified Fast Factorized Backprojection as Applied to X-Band Data for Curved Flight Paths}, booktitle = {European Conference on Synthetic Aperture Radar (EUSAR)}, year = {2008}, pages = {4}, month = {jun}, publisher = {VDE Verlag GmbH}, abstract = {A Fast Factorized Backprojection scheme modified to X-band frequencies and applicable to small aperture beamwidths is presented to compute SAR images from real and synthetic airborne data sets. The numerical complexity and memory consumption of the algorithm is verified and compared to ordinary Backprojection. The modified Fast Factorized Backprojection scheme is investigated for exceedingly curved flight paths and compared to an \u03c9-k algorithm in combination with a motion error correction. Excellent SAR image focusing results were found for the modified Fast Factorized Backprojection approach while keeping the numerical complexity to O(N2log(N)).}, isbn = {978-3-8007-3084-1}, keywords = {SAR Processsing, Time-Domain Back-Projection, TDBP, Back-Projection, Fast Factorized Back-Projection, FFBP, Fast Back-Projection, Synthetic Aperture Radar (SAR), motion compensation, tomography, Airborne SAR,X-Band, Motion Compensation, MoComp, Non-Linear SAR, Non-Linear Flight Tracks}, location = {Friedrichshafen, Germany}, owner = {ofrey}, pdf = {http://www.geo.uzh.ch/~ofrey/protected/PAPERS/brandfassLobiancoEUSAR2008.pdf}, url = {http://www.vde-verlag.de/data/prcd.php?docid=453084017&loc=de} } -
Honglei Chen and D. Kasilingam.
Performance Analysis of Multivariate Super-resolution Processing of Polarimetric Synthetic Aperture Radar Tomography.
In Geoscience and Remote Sensing Symposium, 2008. IGARSS 2008. IEEE International,
volume 4,
pages IV--169--IV--172,
7-11 July 2008.
@INPROCEEDINGS{Chen2008, author = {Honglei Chen and Kasilingam, D.}, title = {Performance Analysis of Multivariate Super-resolution Processing of Polarimetric Synthetic Aperture Radar Tomography}, booktitle = {Geoscience and Remote Sensing Symposium, 2008. IGARSS 2008. IEEE International}, year = {2008}, volume = {4}, pages = {IV--169--IV--172}, month = {7-11 July}, doi = {10.1109/IGARSS.2008.4779684}, owner = {ofrey}, timestamp = {2009.07.01} } -
A. Donnellan,
P. Rosen,
J. Graf,
A. Loverro,
A. Freeman,
R. Treuhaft,
R. Oberto,
M. Simard,
E. Rignot,
R. Kwok,
Xiaoqing Pi,
J.B. Blair,
W. Abdalati,
J. Ranson,
H. Zebker,
B. Hager,
H. Shugart,
M. Fahnestock,
and R. Dubayah.
Deformation, Ecosystem Structure, and Dynamics of Ice (DESDynI).
In Proc. IEEE Aerospace Conf.,
pages 1-13,
March 2008.
Keywords: DESDynl mission, National Research Council Earth Science Decadal Survey, Earth Science Applications from Space, biomass, cryosphere objectives, ecosystem function, ecosystem structure, ice dynamics, integrated L-band InSAR, multibeam Lidar mission, solid Earth, surface deformation, topography, vegetation structure, deformation, optical radar, synthetic aperture radar, topography (Earth), vegetation mapping;.Abstract: The National Research Council Earth Science Decadal Survey, Earth Science Applications from Space, recommends that DESDynl (Deformation, Ecosystem Structure, and Dynamics of Ice), an integrated L-band InSAR and multibeam Lidar mission, launch in the 2010- 2013 timeframe. The mission will measure surface deformation for solid Earth and cryosphere objectives and vegetation structure for understanding the carbon cycle. InSAR has been used to study surface deformation of the solid Earth and cryosphere and more recently vegetation structure for estimates of biomass and ecosystem function. Lidar directly measures topography and vegetation structure and is used to estimate biomass and detect changes in surface elevation. The goal of DESDynl is to take advantage of the spatial continuity of InSAR and precision and directness of Lidar. There are several issues related to the design of the DESDynl mission, including combining the two instruments into a single platform, optimizing the coverage and orbit for the two techniques, and carrying out the science modeling to define and maximize the scientific output of the mission. @INPROCEEDINGS{DonnellanEtAl2008:DESDynI, author={Donnellan, A. and Rosen, P. and Graf, J. and Loverro, A. and Freeman, A. and Treuhaft, R. and Oberto, R. and Simard, M. and Rignot, E. and Kwok, R. and Xiaoqing Pi and Blair, J.B. and Abdalati, W. and Ranson, J. and Zebker, H. and Hager, B. and Shugart, H. and Fahnestock, M. and Dubayah, R.}, booktitle={Proc. IEEE Aerospace Conf.}, title={Deformation, Ecosystem Structure, and Dynamics of Ice ({DESDynI})}, year={2008}, month=mar, volume={}, number={}, pages={1-13}, abstract={The National Research Council Earth Science Decadal Survey, Earth Science Applications from Space, recommends that DESDynl (Deformation, Ecosystem Structure, and Dynamics of Ice), an integrated L-band InSAR and multibeam Lidar mission, launch in the 2010- 2013 timeframe. The mission will measure surface deformation for solid Earth and cryosphere objectives and vegetation structure for understanding the carbon cycle. InSAR has been used to study surface deformation of the solid Earth and cryosphere and more recently vegetation structure for estimates of biomass and ecosystem function. Lidar directly measures topography and vegetation structure and is used to estimate biomass and detect changes in surface elevation. The goal of DESDynl is to take advantage of the spatial continuity of InSAR and precision and directness of Lidar. There are several issues related to the design of the DESDynl mission, including combining the two instruments into a single platform, optimizing the coverage and orbit for the two techniques, and carrying out the science modeling to define and maximize the scientific output of the mission.}, keywords={DESDynl mission;National Research Council Earth Science Decadal Survey, Earth Science Applications from Space;biomass;cryosphere objectives;ecosystem function;ecosystem structure;ice dynamics;integrated L-band InSAR;multibeam Lidar mission;solid Earth;surface deformation;topography;vegetation structure;deformation;optical radar;synthetic aperture radar;topography (Earth);vegetation mapping;}, doi={10.1109/AERO.2008.4526249}, ISSN={1095-323X}, } -
A. Donnellan,
P. Rosen,
J. Ranson,
and H. Zebker.
Deformation, Ecosystem Structure, and Dynamics of Ice (DESDynI).
In IEEE Int. Geoscience and Remote Sensing Symposium, IGARSS 2008,
volume 3,
pages 5-8,
July 2008.
Keywords: DESDynl mission, Deformation, Ecosystem Structure, and Dynamics of Ice, Earth Science Decadal Survey, National Research Council, biomass estimation, carbon cycle, cryosphere objectives, ecosystem function, integrated L-band InSAR, multibeam Lidar mission, solid Earth surface deformation, surface elevation changes, topography measure, vegetation structure, deformation, optical radar, radar interferometry, remote sensing by radar, topography (Earth), vegetation;.Abstract: The National Research Council Earth Science Decadal Survey, Earth Science Applications from Space, recommends that DESDynI (Deformation, Ecosystem Structure, and Dynamics of Ice), an integrated L-band InSAR and multibeam Lidar mission, launch in the 2010-2013 timeframe. The mission will measure surface deformation for solid Earth and cryosphere objectives and vegetation structure for understanding the carbon cycle. InSAR has been used to study surface deformation of the solid Earth and cryosphere and more recently vegetation structure for estimates of biomass and ecosystem function. Lidar directly measures topography and vegetation structure and is used to estimate biomass and detect changes in surface elevation. The goal of DESDynI is to take advantage of the spatial continuity of InSAR and the precision and directness of Lidar. There are several issues related to the design of the DESDynI mission, including combining the two instruments into a single platform, optimizing the coverage and orbit for the two techniques, and carrying out the science modeling to define and maximize the scientific output of the mission. @INPROCEEDINGS{DonnellanRosenRansonZebker2008:DESDynI, author={Donnellan, A. and Rosen, P. and Ranson, J. and Zebker, H.}, booktitle={ IEEE Int. Geoscience and Remote Sensing Symposium, IGARSS 2008}, title={Deformation, Ecosystem Structure, and Dynamics of Ice ({DESDynI})}, year={2008}, month=jul, volume={3}, number={}, pages={5-8}, abstract={The National Research Council Earth Science Decadal Survey, Earth Science Applications from Space, recommends that DESDynI (Deformation, Ecosystem Structure, and Dynamics of Ice), an integrated L-band InSAR and multibeam Lidar mission, launch in the 2010-2013 timeframe. The mission will measure surface deformation for solid Earth and cryosphere objectives and vegetation structure for understanding the carbon cycle. InSAR has been used to study surface deformation of the solid Earth and cryosphere and more recently vegetation structure for estimates of biomass and ecosystem function. Lidar directly measures topography and vegetation structure and is used to estimate biomass and detect changes in surface elevation. The goal of DESDynI is to take advantage of the spatial continuity of InSAR and the precision and directness of Lidar. There are several issues related to the design of the DESDynI mission, including combining the two instruments into a single platform, optimizing the coverage and orbit for the two techniques, and carrying out the science modeling to define and maximize the scientific output of the mission.}, keywords={DESDynl mission;Deformation, Ecosystem Structure, and Dynamics of Ice;Earth Science Decadal Survey;National Research Council;biomass estimation;carbon cycle;cryosphere objectives;ecosystem function;integrated L-band InSAR;multibeam Lidar mission;solid Earth surface deformation;surface elevation changes;topography measure;vegetation structure;deformation;optical radar;radar interferometry;remote sensing by radar;topography (Earth);vegetation;}, doi={10.1109/IGARSS.2008.4779268}, ISSN={}, } -
G. Fornaro,
A. Pauciullo,
F. Lombardini,
and M. Pardini.
Detection of Single and Multiple Scatterers in Multibaseline Multitemporal SAR Data.
In Geoscience and Remote Sensing Symposium, 2008. IGARSS 2008. IEEE International,
volume 2,
pages II--453--II--456,
7-11 July 2008.
@INPROCEEDINGS{Fornaro2008, author = {Fornaro, G. and Pauciullo, A. and Lombardini, F. and Pardini, M.}, title = {Detection of Single and Multiple Scatterers in Multibaseline Multitemporal SAR Data}, booktitle = {Geoscience and Remote Sensing Symposium, 2008. IGARSS 2008. IEEE International}, year = {2008}, volume = {2}, pages = {II--453--II--456}, month = {7-11 July}, doi = {10.1109/IGARSS.2008.4779026}, owner = {ofrey}, timestamp = {2009.07.01} } -
Othmar Frey,
Christophe Magnard,
Maurice Rüegg,
and Erich Meier.
Focusing SAR Data Acquired From Non-Linear Sensor Trajectories.
In IEEE International Geoscience and Remote Sensing Symposium, IGARSS '08,
pages 415-418,
2008.
Keywords: SAR Processing, Time-Domain Back-Projection, Back-Projection, Non-Linear Flight Tracks, Curvilinear SAR, Extended Chirp Scaling, ECS, Mosaicking, Geocoding, Integrated Focusing and Geocoding, Georeferencing, mapping, corridor mapping.E-SAR, L-Band, digital elevation model, Airborne SAR.Abstract: Standard focusing of SAR data assumes a straight recording track of the sensor platform. Small non-linearities of airborne platform tracks are corrected for during a motion compensation step while keeping the assumption of a linear flight path. In the following, the processing of SAR data from nonlinear tracks is discussed as may originate from small aircraft or drones flying at low altitude. They fly not a straight track but one dependent on topography, influences of weather and wind, or dependent on the shape of dedicated areas of interest such as rivers or traffic routes. A time-domain backprojection based technique, is proposed and evaluated with the help of experimental data featuring a drop in height, a double bend, a 90-degree curve and a linear flight track. In order to assess the quality of the focused data, close-ups of amplitude images are compared and the coherence is evaluated. The experimental data was acquired by the German Aerospace Center's E-SAR L-band system. @INPROCEEDINGS{freyMagnardRueeggMeier08Igarss:Tracks, author = {Othmar Frey and Christophe Magnard and Maurice R{\"u}egg and Erich Meier}, title = {{Focusing SAR Data Acquired From Non-Linear Sensor Trajectories}}, booktitle = {IEEE International Geoscience and Remote Sensing Symposium, IGARSS '08}, year = {2008}, pages = {415-418}, abstract = {Standard focusing of SAR data assumes a straight recording track of the sensor platform. Small non-linearities of airborne platform tracks are corrected for during a motion compensation step while keeping the assumption of a linear flight path. In the following, the processing of SAR data from nonlinear tracks is discussed as may originate from small aircraft or drones flying at low altitude. They fly not a straight track but one dependent on topography, influences of weather and wind, or dependent on the shape of dedicated areas of interest such as rivers or traffic routes. A time-domain backprojection based technique, is proposed and evaluated with the help of experimental data featuring a drop in height, a double bend, a 90-degree curve and a linear flight track. In order to assess the quality of the focused data, close-ups of amplitude images are compared and the coherence is evaluated. The experimental data was acquired by the German Aerospace Center's E-SAR L-band system.}, keywords = {SAR Processing, Time-Domain Back-Projection, Back-Projection, Non-Linear Flight Tracks, Curvilinear SAR, Extended Chirp Scaling, ECS, Mosaicking, Geocoding, Integrated Focusing and Geocoding, Georeferencing, mapping, corridor mapping.E-SAR, L-Band, digital elevation model, Airborne SAR}, owner = {ofrey}, pdf = {http://www.geo.uzh.ch/~ofrey/myPublications/PAPERS/freyMagnardRueeggMeier08IgarssTracks.pdf}, url = {http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=4779746&isnumber=4779630} } -
Othmar Frey,
Christophe Magnard,
Maurice Rüegg,
and Erich Meier.
Non-Linear SAR Data Processing By Time-Domain Back-Projection.
In Proc. of EUSAR 2008 - 7th European Conference on Synthetic Aperture Radar,
pages 165-168,
2008.
Keywords: SAR Processing, Time-Domain Back-Projection, Back-Projection, Non-Linear Flight Tracks, Curvilinear SAR, Extended Chirp Scaling, ECS, Mosaicking, Geocoding, Integrated Focusing and Geocoding, Georeferencing, mapping, corridor mapping.E-SAR, L-Band, digital elevation model, Airborne SAR.Abstract: Focusing of conventional stripmap SAR data assumes a straight recording track of the sensor platform. Small deviations from that linear trajectory are corrected by motion compensation steps while keeping the assumption of a linear acquisition path. In the following, the processing of SAR data from non-linear tracks is discussed as may originate from small aircraft or drones flying at low altitude. They fly not a straight track but one dependent on topography, influences of weather and wind, or dependent on the shape of dedicated areas of interest such as rivers or traffic routes. Experimental data featuring a drop in height, a double bend and a 90-degree curve have been processed using a time-domain back-projection approach. The data was acquired by the German Aerospace Center's E-SAR L-band system. @INPROCEEDINGS{freyMagnardRueeggMeier08Eusar:Tracks, author = {Othmar Frey and Christophe Magnard and Maurice R{\"u}egg and Erich Meier}, title = {{Non-Linear SAR Data Processing By Time-Domain Back-Projection}}, booktitle = {Proc. of EUSAR 2008 - 7th European Conference on Synthetic Aperture Radar}, year = {2008}, pages = {165-168}, abstract = {Focusing of conventional stripmap SAR data assumes a straight recording track of the sensor platform. Small deviations from that linear trajectory are corrected by motion compensation steps while keeping the assumption of a linear acquisition path. In the following, the processing of SAR data from non-linear tracks is discussed as may originate from small aircraft or drones flying at low altitude. They fly not a straight track but one dependent on topography, influences of weather and wind, or dependent on the shape of dedicated areas of interest such as rivers or traffic routes. Experimental data featuring a drop in height, a double bend and a 90-degree curve have been processed using a time-domain back-projection approach. The data was acquired by the German Aerospace Center's E-SAR L-band system.}, keywords = {SAR Processing, Time-Domain Back-Projection, Back-Projection, Non-Linear Flight Tracks, Curvilinear SAR, Extended Chirp Scaling, ECS, Mosaicking, Geocoding, Integrated Focusing and Geocoding, Georeferencing, mapping, corridor mapping.E-SAR, L-Band, digital elevation model, Airborne SAR}, owner = {ofrey}, pdf = {http://www.geo.uzh.ch/~ofrey/myPublications/PAPERS/freyMagnardRueeggMeier08EusarTracks.pdf} } -
Othmar Frey and Erich Meier.
Combining Time-Domain Back-Projection and Capon Beamforming for Tomographic SAR Processing.
In IEEE International Geoscience and Remote Sensing Symposium, IGARSS '08,
pages 445-448,
2008.
Keywords: SAR Processing, SAR Tomography, Tomographic Processing, Multi-Baseline SAR, Time-Domain Back-Projection, Back-Projection, E-SAR, P-Band, Forestry, Capon, Capon Beamforming, Superresolution.Abstract: Various tomographic processing methods have been investigated in recent years. The quality of the focused tomographic image is usually limited by several factors. In particular, Fourier-based focusing methods are susceptible to irregular and sparse sampling, two problems that are unavoidable in case of multi-pass, multi-baseline SAR data acquired by an airborne system. Neither time-domain back-projection (TDBP) processing, although providing a very accurate processing framework, is able to overcome the problem of ambiguous target detection in the tomographic image. In this paper, a possible extension of the TDBP approach to multilooking based tomographic focusing methods like standard beamforming and Capon beamforming is discussed. Preliminary results obtained with a simulated and a real airborne tomographic P-band data set are shown. @INPROCEEDINGS{freyMeier08Igarss:Tomo, author = {Othmar Frey and Erich Meier}, title = {{Combining Time-Domain Back-Projection and Capon Beamforming for Tomographic SAR Processing}}, booktitle = {IEEE International Geoscience and Remote Sensing Symposium, IGARSS '08}, year = {2008}, pages = {445-448}, abstract = {Various tomographic processing methods have been investigated in recent years. The quality of the focused tomographic image is usually limited by several factors. In particular, Fourier-based focusing methods are susceptible to irregular and sparse sampling, two problems that are unavoidable in case of multi-pass, multi-baseline SAR data acquired by an airborne system. Neither time-domain back-projection (TDBP) processing, although providing a very accurate processing framework, is able to overcome the problem of ambiguous target detection in the tomographic image. In this paper, a possible extension of the TDBP approach to multilooking based tomographic focusing methods like standard beamforming and Capon beamforming is discussed. Preliminary results obtained with a simulated and a real airborne tomographic P-band data set are shown.}, keywords = {SAR Processing, SAR Tomography, Tomographic Processing, Multi-Baseline SAR, Time-Domain Back-Projection, Back-Projection, E-SAR, P-Band, Forestry, Capon, Capon Beamforming, Superresolution}, owner = {ofrey}, pdf = {http://www.geo.uzh.ch/~ofrey/myPublications/PAPERS/freyMeier08IgarssTomo.pdf}, url = {http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=4779024&isnumber=4778902} } -
Othmar Frey and Erich Meier.
Tomographic Focusing by Combining Time-Domain Back-Projection and Multi-Looking Based Focusing Techniques.
In Proc. of EUSAR 2008 - 7th European Conference on Synthetic Aperture Radar,
pages 73-76,
2008.
Keywords: SAR Processing, SAR Tomography, Tomographic Processing, Multi-Baseline SAR, Time-Domain Back-Projection, Back-Projection, E-SAR, P-Band, Forestry, Capon, Capon Beamforming, Superresolution.Abstract: Various tomographic processing methods have been investigated in recent years. The quality of the focused tomographic image is usually limited by several factors. In particular, Fourier-based focusing methods are susceptible to irregular and sparse sampling, two problems that are unavoidable in case of multi-pass, multi-baseline SAR data acquired by an airborne system. Neither time-domain back-projection (TDBP) processing, although providing a very accurate processing framework, is able to overcome the problem of ambiguous target detection in the tomographic image. In this paper, a possible extension of the TDBP approach to multi-looking based tomographic focusing methods like standard beamforming and Capon beamforming is discussed. @INPROCEEDINGS{freyMeier08Eusar:Tomo, author = {Othmar Frey and Erich Meier}, title = {{Tomographic Focusing by Combining Time-Domain Back-Projection and Multi-Looking Based Focusing Techniques}}, booktitle = {Proc. of EUSAR 2008 - 7th European Conference on Synthetic Aperture Radar}, year = {2008}, pages = {73-76}, abstract = {Various tomographic processing methods have been investigated in recent years. The quality of the focused tomographic image is usually limited by several factors. In particular, Fourier-based focusing methods are susceptible to irregular and sparse sampling, two problems that are unavoidable in case of multi-pass, multi-baseline SAR data acquired by an airborne system. Neither time-domain back-projection (TDBP) processing, although providing a very accurate processing framework, is able to overcome the problem of ambiguous target detection in the tomographic image. In this paper, a possible extension of the TDBP approach to multi-looking based tomographic focusing methods like standard beamforming and Capon beamforming is discussed.}, keywords = {SAR Processing, SAR Tomography, Tomographic Processing, Multi-Baseline SAR, Time-Domain Back-Projection, Back-Projection, E-SAR, P-Band, Forestry, Capon, Capon Beamforming, Superresolution}, owner = {ofrey}, pdf = {http://www.geo.uzh.ch/~ofrey/myPublications/PAPERS/freyMeier08EusarTomo.pdf} } -
Charles V. Jakowatz,
Daniel E. Wahl,
and David A. Yocky.
Beamforming as a foundation for spotlight-mode SAR image formation by backprojection.
In Edmund G. Zelnio and Frederick D. Garber, editors,
,
volume 6970,
pages 69700Q,
2008.
SPIE.
Keywords: SAR Processing, Back-projection, Time-Domain Back-Projection, TDBP, Fast Back-projection, Fast-Factorized Back-Projection, FFBP, Spotlight SAR, Spotlight-mode data, Beamforming.@conference{jakowatzWahlYockyBeamformingTDBPSpotlightMode2008, author = {Charles V. Jakowatz, Jr. and Daniel E. Wahl and David A. Yocky}, editor = {Edmund G. Zelnio and Frederick D. Garber}, collaboration = {}, title = {Beamforming as a foundation for spotlight-mode {SAR} image formation by backprojection}, publisher = {SPIE}, year = {2008}, journal = {Algorithms for Synthetic Aperture Radar Imagery XV}, volume = {6970}, number = {1}, eid = {69700Q}, numpages = {15}, pages = {69700Q}, location = {Orlando, FL, USA}, url = {http://link.aip.org/link/?PSI/6970/69700Q/1}, doi = {10.1117/12.779305}, keywords = {SAR Processing, Back-projection, Time-Domain Back-Projection, TDBP, Fast Back-projection, Fast-Factorized Back-Projection, FFBP, Spotlight SAR, Spotlight-mode data, Beamforming}, pdf = {http://www.geo.uzh.ch/~ofrey/protected/PAPERS/jakowatzWahlYockyBeamformingTDBPSpotlightMode2008.pdf}, owner = {ofrey}, } -
F. Lombardini,
G. Fornaro,
M. Pardini,
D. Reale,
F. Serafino,
F. Soldovieri,
and M. Costantini.
SAR tomography for scene elevation and deformation reconstruction: Algorithms and potentialities.
In Radar Conference, 2008. RADAR '08. IEEE,
pages 1--7,
26-30 May 2008.
@INPROCEEDINGS{Lombardini2008, author = {Lombardini, F. and Fornaro, G. and Pardini, M. and Reale, D. and Serafino, F. and Soldovieri, F. and Costantini, M.}, title = {SAR tomography for scene elevation and deformation reconstruction: Algorithms and potentialities}, booktitle = {Radar Conference, 2008. RADAR '08. IEEE}, year = {2008}, pages = {1--7}, month = {26-30 May}, doi = {10.1109/RADAR.2008.4720739}, owner = {ofrey}, timestamp = {2009.07.01} } -
Christophe Magnard,
Othmar Frey,
Maurice Rüegg,
and Erich Meier.
Improved Airborne SAR Data Processing by Blockwise Focusing, Mosaicking and Geocoding.
In Proc. of EUSAR 2008 - 7th European Conference on Synthetic Aperture Radar,
pages 375-378,
2008.
Keywords: SAR Processing, Time-Domain Back-Projection, Back-Projection, Non-Linear Flight Tracks, Curvilinear SAR, Extended Chirp Scaling, ECS, Mosaicking, Geocoding, Integrated Focusing and Geocoding, Georeferencing, mapping, corridor mapping.E-SAR, L-Band, digital elevation model, Airborne SAR.Abstract: Standard focusing of SAR data assumes a straight recording track of the sensor platform. Small non-linearities of airborne platform are corrected for during a motion compensation step while keeping the assumption of a stripmap geometry. In the case of high resolution and high frequency SAR systems, the navigation data may not be accurate enough to perform such a motion compensation; SAR systems mounted on small aircrafts or drones flying at low altitude do not follow a straight track but one dependent on topography and atmospheric conditions. We present a blockwise focusing, mosaicking and geocoding method which allows processing such data. For the experiments, MEMPHIS and E-SAR data were used. @INPROCEEDINGS{magnardFreyRueeggMeier08Eusar:Tracks, author = {Christophe Magnard and Othmar Frey and Maurice R{\"u}egg and Erich Meier}, title = {{Improved Airborne SAR Data Processing by Blockwise Focusing, Mosaicking and Geocoding}}, booktitle = {Proc. of EUSAR 2008 - 7th European Conference on Synthetic Aperture Radar}, year = {2008}, pages = {375-378}, abstract = {Standard focusing of SAR data assumes a straight recording track of the sensor platform. Small non-linearities of airborne platform are corrected for during a motion compensation step while keeping the assumption of a stripmap geometry. In the case of high resolution and high frequency SAR systems, the navigation data may not be accurate enough to perform such a motion compensation; SAR systems mounted on small aircrafts or drones flying at low altitude do not follow a straight track but one dependent on topography and atmospheric conditions. We present a blockwise focusing, mosaicking and geocoding method which allows processing such data. For the experiments, MEMPHIS and E-SAR data were used.}, keywords = {SAR Processing, Time-Domain Back-Projection, Back-Projection, Non-Linear Flight Tracks, Curvilinear SAR, Extended Chirp Scaling, ECS, Mosaicking, Geocoding, Integrated Focusing and Geocoding, Georeferencing, mapping, corridor mapping.E-SAR, L-Band, digital elevation model, Airborne SAR}, owner = {ofrey}, pdf = {http://www.geo.uzh.ch/~ofrey/myPublications/PAPERS/magnardFreyRueeggMeier08EusarTracks.pdf} } -
G. Margarit,
J.J. Mallorqui,
I. Corney,
and C. Lopez-Martinez.
A Public Database of Simulated Multidimensional SAR Data for Techniques Validation.
In Geoscience and Remote Sensing Symposium, 2008. IGARSS 2008. IEEE International,
volume 2,
pages II--601--II--604,
7-11 July 2008.
@INPROCEEDINGS{Margarit2008, author = {Margarit, G. and Mallorqui, J.J. and Corney, I. and Lopez-Martinez, C.}, title = {A Public Database of Simulated Multidimensional SAR Data for Techniques Validation}, booktitle = {Geoscience and Remote Sensing Symposium, 2008. IGARSS 2008. IEEE International}, year = {2008}, volume = {2}, pages = {II--601--II--604}, month = {7-11 July}, doi = {10.1109/IGARSS.2008.4779064}, owner = {ofrey}, timestamp = {2009.07.01} } -
Matteo Nannini,
Rolf Scheiber,
and Alberto Moreira.
On the Minimum Number of Tracks for SAR Tomography.
In ,
volume 2,
pages 441-444,
July 2008.
Keywords: SAR Processing, SAR Tomography, Capon, MUSIC, image reconstruction, airboren SAR, image representation, radar interferometry, synthetic aperture radar3D representation, German Aerospace Center, DLR, L-band, SAR interferometry, SARTom, data acquisition, equivalent targets, experimental SAR system, minimum tomographic aperture, spheroidal wave functions, subspace superresolution methods, synthetic aperture radar tomography, tracks minimum number determination, volumetric source, ESAR.Abstract: The main drawback of SAR Tomography (SARTom) is the considerable number of tracks required to achieve the 3-dimensional (3D) representation of a viewed scene. The key point concerns the trade-off between the vertical resolution and the control on ambiguities phenomena. This paper deals with the problem of the determination of the minimum number of required tracks when super-resolution subspace methods are applied. The results are validated on real data acquired in L-band by the E-SAR system of the German Aerospace Centre. @INPROCEEDINGS{nanniniScheiberMoreira2008:SARTom, author = {Nannini, Matteo and Scheiber, Rolf and Moreira, Alberto}, title = {{On the Minimum Number of Tracks for SAR Tomography}}, year = {2008}, volume = {2}, pages = {441-444}, month = {July}, abstract = {The main drawback of SAR Tomography (SARTom) is the considerable number of tracks required to achieve the 3-dimensional (3D) representation of a viewed scene. The key point concerns the trade-off between the vertical resolution and the control on ambiguities phenomena. This paper deals with the problem of the determination of the minimum number of required tracks when super-resolution subspace methods are applied. The results are validated on real data acquired in L-band by the E-SAR system of the German Aerospace Centre.}, doi = {10.1109/IGARSS.2008.4779023}, journal = {IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2008.}, keywords = {SAR Processing, SAR Tomography, Capon, MUSIC, image reconstruction, airboren SAR, image representation, radar interferometry, synthetic aperture radar3D representation, German Aerospace Center, DLR, L-band, SAR interferometry, SARTom, data acquisition, equivalent targets, experimental SAR system, minimum tomographic aperture, spheroidal wave functions, subspace superresolution methods, synthetic aperture radar tomography, tracks minimum number determination, volumetric source, ESAR}, owner = {ofrey}, pdf = {http://www.geo.uzh.ch/~ofrey/protected/PAPERS/nanniniScheiberMoreira2008.pdf}, url = {http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=4779023&isnumber=4778902} } -
P.A. Rosen,
S. Hensley,
and C. Le.
Observations and mitigation of RFI in ALOS PALSAR SAR data: Implications for the DESDynI mission.
In IEEE Radar Conference,
pages 1-6,
May 2008.
Keywords: DESDynI mission, L-band polarimetric radar, RFI, SAR data, radio frequency interference, synthetic aperture radar, radiofrequency interference, synthetic aperture radar;.Abstract: Initial examination of ALOS PALSAR synthetic aperture radar (SAR) data has indicated significant radio frequency interference (RFI) in several geographic locations around the world. RFI causes significant reduction in image contrast, introduces periodic and quasi-periodic image artifacts, and introduces significant phase noise in repeat-pass interferometric data reduction. The US National Research Council Decadal Survey of Earth Science has recommended DESDynI, a Deformation, Ecosystem Structure, and Dynamics of Ice satellite mission comprising an L-band polarimetric radar configured for repeat-pass interferometry. There is considerable interest internationally in other future L-band and lower frequency systems, as well. Therefore, the issues of prevalence and possibilities of mitigation of RFI in these crowded frequency bands are of considerable interest. RFI is observed in ALOS PALSAR in California and Hawaii, USA, and in southern Egypt in data examined to date. Application of several techniques for removing it from the data prior to SAR image formation, ranging from straight-forward spectral normalization to time-domain, multi-phase filtering techniques, are considered. Considerable experience has been gained from the removal of RFI from P-band acquired by the GeoSAR system. These techniques applied to the PALSAR data are most successful when the bandwidth of any particular spectral component of the RFI is narrow. Performance impacts for SAR imagery and interferograms are considered in the context of DESDynI measurement requirements. @INPROCEEDINGS{RosenHensleyLe2008:DESDynIandRFI, author={Rosen, P.A. and Hensley, S. and Le, C.}, booktitle={IEEE Radar Conference}, title={Observations and mitigation of RFI in ALOS PALSAR SAR data: Implications for the DESDynI mission}, year={2008}, month={may}, volume={}, number={}, pages={1-6}, abstract={Initial examination of ALOS PALSAR synthetic aperture radar (SAR) data has indicated significant radio frequency interference (RFI) in several geographic locations around the world. RFI causes significant reduction in image contrast, introduces periodic and quasi-periodic image artifacts, and introduces significant phase noise in repeat-pass interferometric data reduction. The US National Research Council Decadal Survey of Earth Science has recommended DESDynI, a Deformation, Ecosystem Structure, and Dynamics of Ice satellite mission comprising an L-band polarimetric radar configured for repeat-pass interferometry. There is considerable interest internationally in other future L-band and lower frequency systems, as well. Therefore, the issues of prevalence and possibilities of mitigation of RFI in these crowded frequency bands are of considerable interest. RFI is observed in ALOS PALSAR in California and Hawaii, USA, and in southern Egypt in data examined to date. Application of several techniques for removing it from the data prior to SAR image formation, ranging from straight-forward spectral normalization to time-domain, multi-phase filtering techniques, are considered. Considerable experience has been gained from the removal of RFI from P-band acquired by the GeoSAR system. These techniques applied to the PALSAR data are most successful when the bandwidth of any particular spectral component of the RFI is narrow. Performance impacts for SAR imagery and interferograms are considered in the context of DESDynI measurement requirements.}, keywords={DESDynI mission,L-band polarimetric radar;RFI;SAR data;radio frequency interference;synthetic aperture radar;radiofrequency interference;synthetic aperture radar;}, doi={10.1109/RADAR.2008.4720738}, ISSN={1097-5659}, } -
Stefano Tebaldini.
Forest SAR tomography: A covariance matching approach.
In IEEE Radar Conference, 2008. RADAR '08.,
pages 1-6,
May 2008.
Keywords: SAR Processing, SAR Tomography, Tomography, E-SAR, P-Band, radar imaging, radar interferometry, radar polarimetry, radar resolution, synthetic aperture radar, tomographyP-band SAR images, covariance matching approach, forest SAR tomography, multipolarimetric channel data, single polarimetric channel data, single target interferometric analysis, synthetic aperture radar interferometry, system resolution cell.Abstract: In this paper a technique to conduct tomographic analyses of forested areas through multiple, coherent SAR images is presented. This technique differs from other methods existing in literature in that it may be regarded as a natural extension of SAR interferometry to the case where several distributed targets are present within the system resolution cell. In this way, it is possible to estimate the position of each target in the resolution cell with virtually the same accuracy obtainable by a single target interferometric analysis. Furthermore, this approach is suited to both single and multi polarimetric channel data. As a validation, this paper reports the results of a tomographic analysis of the forest site of Remningstorp, Sweden, basing on a data-set of 9 P-band SAR images acquired by DLRpsilas E-SAR. @INPROCEEDINGS{tebaldiniRADAR2008:Tomo, author = {Tebaldini, Stefano}, title = {Forest SAR tomography: A covariance matching approach}, booktitle = {IEEE Radar Conference, 2008. RADAR '08. }, year = {2008}, pages = {1-6}, month = {may}, abstract = {In this paper a technique to conduct tomographic analyses of forested areas through multiple, coherent SAR images is presented. This technique differs from other methods existing in literature in that it may be regarded as a natural extension of SAR interferometry to the case where several distributed targets are present within the system resolution cell. In this way, it is possible to estimate the position of each target in the resolution cell with virtually the same accuracy obtainable by a single target interferometric analysis. Furthermore, this approach is suited to both single and multi polarimetric channel data. As a validation, this paper reports the results of a tomographic analysis of the forest site of Remningstorp, Sweden, basing on a data-set of 9 P-band SAR images acquired by DLRpsilas E-SAR.}, doi = {10.1109/RADAR.2008.4721084}, issn = {1097-5659}, keywords = {SAR Processing, SAR Tomography, Tomography, E-SAR, P-Band, radar imaging, radar interferometry, radar polarimetry, radar resolution, synthetic aperture radar, tomographyP-band SAR images, covariance matching approach, forest SAR tomography, multipolarimetric channel data, single polarimetric channel data, single target interferometric analysis, synthetic aperture radar interferometry, system resolution cell}, owner = {ofrey}, pdf = {http://www.geo.uzh.ch/~ofrey/protected/PAPERS/tebaldiniRADAR2008.pdf}, url = {http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=4721084&isnumber=4720717&tag=1} } -
Stefano Tebaldini,
Fabio Rocca,
and A Monti-Guarnieri.
Model Based SAR Tomography of Forested Areas.
In IEEE International Geoscience and Remote Sensing Symposium,
volume 2,
pages 593--596,
July 2008.
Keywords: SAR Processing, SAR Tomography, Tomography, E-SAR, P-Band.Abstract: In this paper a technique is described for the tomographic characterization of forested areas through multiple SAR observations. This technique is based on a model of the second order statistics of the multi baseline, multi polarimetric, data which accounts for the presence of multiple distributed targets within the system resolution cell. The results of an experiment performed on a real P-band, multi-baseline, fully polarimetric data set relative to the forested site of Remningstorp, Sweden, are reported. Such results show the feasibility of performing a model based tomographic analysis of forests, resulting in a characterization of both the ground and the canopy in terms of elevation, spatial structure, and scattered power. @INPROCEEDINGS{tebaldiniRoccaGuarnieri2008:Tomo, author = {Tebaldini, Stefano and Rocca, Fabio and Monti-Guarnieri, A}, title = {Model Based {SAR} Tomography of Forested Areas}, booktitle = {IEEE International Geoscience and Remote Sensing Symposium}, year = {2008}, volume = {2}, pages = {593--596}, month = {jul}, abstract = {In this paper a technique is described for the tomographic characterization of forested areas through multiple SAR observations. This technique is based on a model of the second order statistics of the multi baseline, multi polarimetric, data which accounts for the presence of multiple distributed targets within the system resolution cell. The results of an experiment performed on a real P-band, multi-baseline, fully polarimetric data set relative to the forested site of Remningstorp, Sweden, are reported. Such results show the feasibility of performing a model based tomographic analysis of forests, resulting in a characterization of both the ground and the canopy in terms of elevation, spatial structure, and scattered power.}, doi = {10.1109/IGARSS.2008.4779062}, keywords = {SAR Processing, SAR Tomography, Tomography, E-SAR, P-Band}, owner = {ofrey}, pdf = {http://www.geo.uzh.ch/~ofrey/protected/PAPERS/tebaldiniRoccaGuarnieri2008.pdf}, url = {http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=4779062&isnumber=4778902} } -
Daniel E. Wahl,
David A. Yocky,
and Charles V. Jakowatz.
An implementation of a fast backprojection image formation algorithm for spotlight-mode SAR.
In Edmund G. Zelnio and Frederick D. Garber, editors,
,
volume 6970,
pages 69700H,
2008.
SPIE.
Keywords: SAR Processing, Back-projection, Time-Domain Back-Projection, TDBP, Fast Back-projection, Fast-Factorized Back-Projection, FFBP, Spotlight SAR, Spotlight-mode data.@conference{wahlYockyJakowatzFastBackprojectionSpotlight2008, author = {Daniel E. Wahl and David A. Yocky and Charles V. Jakowatz, Jr.}, editor = {Edmund G. Zelnio and Frederick D. Garber}, collaboration = {}, title = {An implementation of a fast backprojection image formation algorithm for spotlight-mode {SAR}}, publisher = {SPIE}, year = {2008}, journal = {Algorithms for Synthetic Aperture Radar Imagery XV}, volume = {6970}, number = {1}, eid = {69700H}, numpages = {11}, pages = {69700H}, location = {Orlando, FL, USA}, url = {http://link.aip.org/link/?PSI/6970/69700H/1}, doi = {10.1117/12.779401}, keywords = {SAR Processing, Back-projection, Time-Domain Back-Projection, TDBP, Fast Back-projection, Fast-Factorized Back-Projection, FFBP, Spotlight SAR, Spotlight-mode data}, pdf = {http://www.geo.uzh.ch/~ofrey/protected/PAPERS/wahlYockyJakowatzFastBackprojectionSpotlight2008.pdf}, owner = {ofrey}, } -
Yanping Wang,
Bin Wang,
Wen Hong,
Lei Du,
and Yirong Wu.
Imaging Geometry Analysis of 3D SAR using Linear Array Antennas.
In IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2008,
volume 3,
pages 1216-1219,
July 2008.
Keywords: SAR Processing, SAR Tomography, Tomography, linear antenna arrays, radar imaging, radar interferometry, synthetic aperture radar, 3D SAR, elevation direction, imaging geometry analysis, linear array antennas, signal model.Abstract: Linear array antennas SAR has a resolving capability in the elevation direction, and can get the 3D image of the target. In this paper, we derive the signal model of 3D SAR using a linear array antenna, and get the 3D resolutions and 3D point spread function of array antenna SAR, at the same time the sampling space of array antennas is given. The variance of the resolution in the elevation direction with array antenna angle and referenced look angle is studied. The geometry to reach the best resolution in the elevation direction is analyzed. Meanwhile the resolution for horizontal and vertical antenna array are calculated and compared. @INPROCEEDINGS{wangWangHongDuWu2008:SARTom, author = {Yanping Wang and Bin Wang and Wen Hong and Lei Du and Yirong Wu}, title = {{Imaging Geometry Analysis of 3D SAR using Linear Array Antennas}}, booktitle = {IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2008}, year = {2008}, volume = {3}, pages = {1216-1219}, month = {jul}, abstract = {Linear array antennas SAR has a resolving capability in the elevation direction, and can get the 3D image of the target. In this paper, we derive the signal model of 3D SAR using a linear array antenna, and get the 3D resolutions and 3D point spread function of array antenna SAR, at the same time the sampling space of array antennas is given. The variance of the resolution in the elevation direction with array antenna angle and referenced look angle is studied. The geometry to reach the best resolution in the elevation direction is analyzed. Meanwhile the resolution for horizontal and vertical antenna array are calculated and compared.}, doi = {10.1109/IGARSS.2008.4779576}, keywords = {SAR Processing, SAR Tomography, Tomography, linear antenna arrays, radar imaging, radar interferometry, synthetic aperture radar, 3D SAR, elevation direction, imaging geometry analysis, linear array antennas, signal model}, owner = {ofrey}, pdf = {http://www.geo.uzh.ch/~ofrey/protected/PAPERS/wangWangHongDuWu2008.pdf}, url = {http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=4779576&isnumber=4779256} } -
E.C. Zaugg and D.G. Long.
Along-Track Resolution Enhancement Forwide-Bandwidth, Low-Frequency SAR by Accounting for the Wavelength Change over the Bandwidth.
In Geoscience and Remote Sensing Symposium, 2008. IGARSS 2008. IEEE International,
volume 4,
pages IV--1272--IV--1275,
7-11 July 2008.
Keywords: SAR Processing.@INPROCEEDINGS{Zaugg2008, author = {Zaugg, E.C. and Long, D.G.}, title = {Along-Track Resolution Enhancement Forwide-Bandwidth, Low-Frequency SAR by Accounting for the Wavelength Change over the Bandwidth}, booktitle = {Geoscience and Remote Sensing Symposium, 2008. IGARSS 2008. IEEE International}, year = {2008}, volume = {4}, pages = {IV--1272--IV--1275}, month = {7-11 July}, doi = {10.1109/IGARSS.2008.4779962}, keywords = {SAR Processing}, owner = {ofrey} }
Internal reports
-
Candidate Earth Explorer Core Mission BIOMASS - Report for Assessment.
Technical report,
ESA SP-1313/2,
November 2008.
Keywords: BIOMASS mission, Earth explorer core mission candidate, P-band, forest area, forest biomass, forest disturbances, frequency 425 MHz, global maps, synthetic aperture radar, terrestrial carbon cycle, remote sensing by radar, spaceborne radar, synthetic aperture radar.@TECHREPORT{BIOMASS_ESA_EARTH_EXPLORER_MISSION2008, title={Candidate {Earth} Explorer Core Mission {BIOMASS} - Report for Assessment}, url = {http://esamultimedia.esa.int/docs/SP1313-2_BIOMASS.pdf}, month = nov, year = 2008, address = {ESA SP-1313/2}, keywords={BIOMASS mission;Earth explorer core mission candidate;P-band; forest area;forest biomass;forest disturbances;frequency 425 MHz; global maps;synthetic aperture radar;terrestrial carbon cycle; remote sensing by radar;spaceborne radar;synthetic aperture radar}, }
Miscellaneous
-
Andreas Reigber.
Multimodale Verarbeitung hochauflösender SAR Daten,
February 2008.
Note: Habilitationsschrift an der Fakultät IV -Elektrotechnik un Informatik - der Technischen Universität Berlin.
Keywords: SAR Processing, airborne SAR, omega-k, Range Migration Algorithm, Wave Number Domain Algorithm, Extended Chirp Scaling, ECS, SAR Interferometry, Interferometry, InSAR, Residual Motion Errors, Residual Errors, Motion Compensation, MoComp, PolInSAR, Polarimetry.Abstract: Abbildende Radartechnik ist ein Fernerkundungsverfahren, welches das Ziel hat, von einer beobachteten Gegend eine hochaufgel\"oste Reflektivit\"atskarte im Mikrowellenbereich zu erzeugen. Erreicht wird dies durch Abstrahlung und Empfang von elektromagnetischer Strahlung im Mikrowellenbereich, typischerweise durch Sensoren, die auf Flugzeugen oder Satelliten montiert sind. Unter einer ganzen Reihe von Mikrowellensensoren hat sich in den letzten Jahren ein besonderes Interesse in Radar mit synthetischer Apertur (SAR) herausgebildet. Der Grund hierf\"ur ist, dass das SAR als einziger Mikrowellensensor eine fl\"achige Abbildung mit einer hohen r\"aumlichen Aufl\"osung, die durchaus mit der optischer Systeme vergleichbar ist, erm\"oglicht. Die Entwicklungsgeschichte des Radars mit synthetischer Apertur begann bereits vor \"uber 50 Jahren mit der Idee, die Doppler-Verschiebung des Radarsignals zu nutzen, um die Azimutaufl\"osung des damals aktuellen side-looking airborne radar (SLAR) zu verbessern [215]. Zur Prozessierung der Daten war man, bis in die 1970er Jahre hinein, auf die Verwendung optischer, holographischer Verfahren angewiesen; erst danach war man in der Lage, mittels digitaler Datenverarbeitung hochaufgel\"oste SAR Aufnahmen in hoher Qualit\"at zu erzeugen [10],[216]. Seitdem entwickelte sich die Fernerkundung mit SAR Sensoren rasant weiter, hin zu immer h\"oheren Aufl\"osungen und Aufnahmemodi. In den letzten 10 Jahren gewannen dabei vor allem die mehrkanalige SAR Modi stark an Bedeutung, wie z.B. multispektrales SAR [66], SAR Interferometrie [8] und SAR Polarimetrie [13]. Diese Arbeit besch\"aftigt sich vor allem mit speziellen Datenverarbeitungstechniken solcher mehrkanaliger SAR Daten. SAR Sensoren arbeiten im Mikrowellenbereich des elektromagnetischen Spektrums bei Wellenl\"angen zwischen wenigen Millimetern und mehreren Metern. Betrachtet man das Transmissionsspektrum der Erdatmosph\"are, so stellt man fest, dass bei Wellenl\"angen gr\"osser als etwa 1cm praktisch keine nennenswerte Absorption mehr auftritt. Dies gilt sowohl f\"ur die Luft selbst als auch f\"ur Wolken und kleinere Wassertropfen. SAR Aufnahmen lassen sich daher praktisch unabh\"angig von den aktuell herrschenden Wetterbedingungen generieren, wohingegen Wolken und Nebel f\"ur optische Systeme oft eine grosse Einschr\"ankung darstellen. Als aktives System, das seine eigene Beleuchtung mitbringt, besteht weiterhin keinerlei Abh\"angigkeit von der jeweiligen Tageszeit. Zusammengenommen f\"uhren diese Punkte dazu, dass sich SAR Sensoren besonders gut f\"ur verl\"assliche und regelm\"assige Beobachtungen eignen. Der Informationsgehalt von Radaraufnahmen ist deutlich anders gelagert als der von optischen oder Infrarotsystemen. W\"ahrend im optischen Bereich vor allem die molekulare Zusammensetzung des Objekts f\"ur die charakteristische Reflektivit\"at des Objekts verantwortlich zeichnet, sind im Mikrowellenbereich vor allem die geometrische Form sowie die dielektrischen Eigenschaften f\"ur die St\"arke der R\"uckstreuung von Bedeutung. In Radaraufnahmen tritt daher das Relief und morphologische Strukturen besonders deutlich hervor. Auch \"Anderungen in der Leitf\"ahigkeit, z.B. durch unterschiedliche Bodenfeuchte, k\"onnen so beobachtet werden. Aufgrund der Sensitivit \"at auf dielektrische Eigenschaften k\"onnen im Prinzip sogar Informationen \"uber den Vegetationszustand gesammelt werden. Eine weitere wichtige Eigenschaft von Radaraufnahmen ergibt sich aus den Ausbreitungseigenschaften von Mikrowellen: Durch ihre lange Wellenl\"ange sind Mikrowellen bis zu einem gewissen Grad in der Lage, in Vegetationsschichten, in Schnee und Eis und sogar in den Boden einzudringen [203]. Das Eindringverm\"ogen h\"angt dabei von der Wellenl\"ange des Sensors, aber auch von den dielektrischen Eigenschaften und der Leitf\"ahigkeit des Objekts ab. K\"urzere Wellenl\"angen, wie das X-Band, werden stark ged\"ampft und daher vor allem von der Oberfl\"ache reflektiert. In k\"urzeren Wellenl\"angen sammelt man daher in erster Linie Informationen \"uber die oberen Schichten von Vegetation oder Boden. L\"angere Wellenl\"angen, wie L- oder P-Band, dringen hingegen oft tief in Vegetation ein. R\"uckstreuung in solchen Wellenl\"angen enthalten daher Anteile aus dem gesamten r\"uckstreuenden Volumen. An dieser Stelle zeigt sich bereits ein typisches Problem der Fernerkundung im allgemeinen: Die zu untersuchenden Objekte sind meist recht komplex, und ihre Eigenschaften wirken sich in vielerlei Weise auf das gemessene Bildergebnis aus. Ein Fernerkundungssensor liefert aber nur einen sehr niedrigdimensionalen Raum von Observablen, im Falle eines konventionellen SAR Sensors sogar nur einen einzigen Messwert. Es ist daher in vielen F\"allen sehr schwierig, oder sogar unm\"oglich, aus dem gemessenen Bildergebnis auf den gesuchten Objektparameter zu schliessen. Es besteht also ein Mehrdeutigkeitsproblem: Mehrere verschiedene S\"atze von Objektparametern k\"onnen zu exakt dem gleichem Satz an Observablen f\"uhren. Der einzige Weg dieses Problem zu umgehen, ist die Erh\"ohung der Dimensionalit\"at des Sensors, also die Verwendung mehrerer unabh\"angiger Empfangskan\"ale. Thema dieser Arbeit sind spezielle sogenannte multimodale Verarbeitungstechniken, die f\"ur die korrekte Bearbeitung solcher multidimensionaler Datens\"atze notwendig sind. Es soll dabei insbesondere aufgezeigt werden, dass durch Hinzunahme weiterer Datendimensionen generell eine verbesserte Informationsextraktion erreicht, bzw. mit ihnen eine verbesserte Datenverarbeitung erzielt werden kann. Generell ergeben sich in der SAR Fernerkundung vor allem folgende M\"oglichkeiten f\"ur multimodale Erweiterungen: Multifrequentes SAR: Alle bislang betriebenen satellitengest\"utzten SAR Systeme arbeiten nur in einem einzigen Band, besitzen also eine dedizierte zentrale Wellenl\"ange. Verwendet wird dabei meist das C-Band, wie z.B. bei den europ\"aischen ERS-1, ERS-2 [4] und ENVISAT [119] und den kanadischen RADARSAT-1 [161] und RADARSAT-2 [125]. Es kommt aber auch L-Band, z.B. beim japanischen ALOS-PALSAR [99], und X-Band, wie bei in K\"urze startenden TerraSAR-X [214], zum Einsatz. Prinzipiell stehen daher also SAR Daten in verschiedenen Wellenl\"angen zur Verf\"ugung. Trotzdem sind solche inhomogenen Datenquellen als nicht ideal anzusehen, da unterschiedliche Aufnahmezeitpunkte, sowie abweichende Bildaufl\"osungen und Sensorcharakteristika zu beachten sind. Die einzige Ausnahme stellen die Shuttle Missionen SIR-C/X-SAR im Jahr 1994 (X-, C- und L-Band) [92] und SRTM im Jahr 2000 (X- und C-Band) [213] dar, bei denen zum ersten Mal aus dem Orbit multifrequente SAR Daten simultan aufgezeichnet wurden. Im Gegensatz dazu bieten die allermeisten heutzutage betriebenen flugzeuggest\"utzten SAR Systeme die M\"oglichkeit mehrerer Wellenl\"angen. Zu nennen sind hier beispielsweise das E-SAR System des Deutschen Zentrums f\"ur Luft- und Raumfahrt (X-, C-, S-, L- und P-Band) [89], das franz\"osische RAMSES System von Onera (W-, Ka-, Ku-, X-, C-, S-, L- und P-Band) [45] oder das amerikanische AIRSAR System des JPLs (X-, C- und L-Band) [207]. Die Reflektivit\"at im Mikrowellenbereich kann stark von der verwendeten Wellenl\"ange abh\"angen, da die Dielektrizit\"atskonstante vieler Materialien stark frequenzabh\"angig ist [203]. Auch die Oberfl\"achenrauhigkeit hat in verschiedenen Wellenl\"angen einen unterschiedlichen Einfluss auf die St\"arke der R\"uckstreuung [203]. Aus diesen Gr\"unden erscheinen SAR Aufnahmen, die in unterschiedlichen B\"andern angefertigt worden sind, oft sehr verschieden. Genau diese Unterschiede erlauben es mache Oberfl\"achen oder Materialien zu trennen, die bei Betrachtung in nur einer Wellenl\"ange noch identisch erscheinen; dies l\"asst sich z.B. zu Klassifikationszwecken ausnutzen. Wie bereits zuvor erw\"ahnt, \"andert sich mit der Wellenl\"ange auch das Eindringverm\"ogen der Mikrowellen. Es wird in verschiedenen B\"andern also auch Informationen aus unterschiedlichen Schichten eines Volumens gewonnen; dies kann dazu benutzt werden um beispielsweise in Kombination mit interferometrischen Ans\"atzen Vegetationsh\"ohen zu bestimmen [217][205]. Dadurch dass sich die verschiedenen B\"ander im allgemeinen nicht spektral \"uberlappen, sind multifrequente SAR Daten untereinander inkoh\"arent. Die Datenverarbeitung der einzelnen Kan\"ale erfolgt daher in erster Linie unabh\"angig voneinander; erst zum Schluss werden die verschiedenen Aufnahmen kombiniert ausgewertet. In dieser Arbeit wird aus diesem Grund nicht weiter auf die Verarbeitung multifrequenter Daten eingegangen. Polarimetrisches SAR: Die SAR Polarimetrie (PolSAR) ist eine weitere wichtige M\"oglichkeit, den Beobachtungsraum von SAR Sensoren zu erweitern. Elektromagnetische Wellen sind transversaler Natur und erlauben daher zwei orthogonale Schwingungsrichtungen. Dies gilt sowohl f\"ur den Sende- als auch f\"ur den Empfangskanal, man erh\"alt also im Idealfall 4 unabh\"angige Messungen. Dies ist Gegenstand der Radarpolarimetrie, initiiert im Jahre 1948 durch G.W. Sinclair mit der Einf\"uhrung des Konzepts der Streumatrizen [188]. Da Radarpolarimetrie deutlich h\"ohere Hardwareanforderungen stellt, blieb sie lange nur ein theoretisches Konstrukt [90] [12], und ihr praktischer Nutzen wurde vor allem im zivilen Bereich lange nicht erkannt. Diese Situation \"anderte sich mit der Verf\"ugbarkeit polarimetrischer SAR Daten verschiedener flugzeuggest \"utzter SAR Systeme, wie beispielsweise dem AIRSAR oder dem E-SAR, sowie den beiden SIR-C/X-SAR Missionen, bei denen polarimetrische SAR Daten in mehreren Wellenl\"angen erzeugt wurden. Seitdem hat sich die SAR Polarimetrie zu einer etablierten Fernerkundungsmethode entwickelt, welche auch in zunehmenden Masse von den neuesten SAR Satelliten, wie dem kanadischen RADARSAT-2, dem japanischen ALOS-PALSAR und dem deutschen TerraSAR-X, unterst\"utzt wird. Eine besondere Eigenschaft der SAR Polarimetrie ist die prinzipielle M\"oglichkeit, verschiedenartige R\"uckstreumechanismen unterscheiden zu k\"onnen. Dies kann erreicht werden, da die gemessenen polarimetrischen Signaturen stark vom jeweils aufgetretenen Streuprozess abh\"angen. Im Vergleich zum herk\"ommlichen einkanaligen SAR ergibt sich damit eine signifikante Verbesserung bei der Unterscheidung verschiedener Oberfl\"achentypen, was sich beispielsweise in der Verbesserung von Landnutzungsklassifikationen [35],[111] ausn\"utzen l\"asst. Des weiteren erlaubt die SAR Polarimetrie durch ihren vergr\"osserten Raum an Observablen auch einfache physikalische Modellierungen. Durch Invertierung polarimetrischer Streumodelle lassen sich z.B. Bodenparameter wie Rauigkeit und Bodenfeuchte bestimmen [30]. Weiterhin lassen sich mit Hilfe der SAR Polarimetrie auch die Anteile verschiedener charakteristischer R\"uckstreuklassen ermitteln [65], selbst wenn sie sich innerhalb eines Pixels gegenseitig \"uberlagern. In Kapitel 3 wird auf die Besonderheiten der Verarbeitung polarimetrischer SAR Daten eingegangen. Aufbauend auf die grundlegenden Konzepte der SAR Polarimetrie, zusammengefasst in Abschnitt 3.1, wird in Abschnitt 3.2 eine Zeit-Frequenz Analyse polarimetrischer Daten vorgenommen. Der hierdurch weiter vergr\"osserter Raum an Observablen erlaubt die Detektion st\"orender anisotroper R\"uckstreumechanismen sowie die Entfernung ihres Einflusses aus den Daten. Des weiteren wird in Abschnitt 3.1.2 ein verbessertes polarimetrisches Klassifikationsverfahren unter Verwendung von Nachbarschaftsinformation als zus\"atzlicher Datendimension abgeleitet. Interferometrisches SAR: SAR Interferometrie (InSAR) ist eine multimodale Erweiterung in der SAR Fernerkundung, welche den Beobachtungsraum geometrisch durch mehrere Aufnahmen von leicht verschiedenen Orten erweitert. Anschaulich wird in der SAR Interferometrie eine leichte Variation des Einfallswinkels vorgenommen, wobei davon ausgegangen wird, dass sich die R\"uckstreueigenschaften dabei nicht signifikant ver\"andern. Analysiert wird dann der aufgetretene Phasenunterschied zwischen zwei oder mehreren solcher Aufnahmen, der einen direkten Zusammenhang zu der Topographie des Bodens aufweist und sich daher zur Erstellung von genauen H\"ohenmodellen eignet. Die ersten Experimente in diese Richtung wurden 1974 von L.C. Graham durchgef\"uhrt [79] und in den 1980ern experimentell in Form von InSAR Modifikationen am AIRSAR Sensor fortgef\"uhrt [220]. Popul\"ar wurde die SAR Interferometrie aber erst mit dem Start der ERS Satelliten, die erstmals operationelle satellitengest\"utzte SAR Interferometrie bieten konnten. Im Jahr 2000 kumulierte diese Entwicklung in der Shuttle Radar Topography Mission (SRTM), w\"ahrend der ein hochgenaues H\"ohenmodell der gesamten Landoberfl\"ache der Erde zwischen 60 deg N und 60 deg S erzeugt wurde [213]. Die SAR Interferometrie ist heutzutage eine etablierte Technik, welche mit einer Vielzahl von satellitengest\"utzten Sensoren m\"oglich ist [68][72][128]. Neben der Abbildung der Terraintopographie kann die SAR Interferometrie auch zur Bestimmung kleinster Topographie\"anderungen eingesetzt werden. Mit dieser sogenannten differentiellen SAR Interferometrie (DInSAR) lassen sich durch Phasenmessung Genauigkeiten unterhalb der Wellenl\"ange, also typischerweise bis in den Millimeterbereich hinein, erzielen. Dies ist in verschiedensten Anwendungsbereichen einsetzbar, wie z.B. in der Analyse tektonischer Prozesse, oder in der Beobachtung von Absenkungsprozessen als Folge menschlicher Bergbauaktivit\"aten [124],[48],[105]. Des weiteren l\"asst sich der erweiterte Beobachtungsraum der SAR Interferometrie auch mit dem der SAR Polarimetrie verschneiden [142]. In der sogenannten polarimetrischen SAR Interferometrie (PolInSAR) wird dies ausgenutzt, um physikalische R\"uckstreumodelle mehrerer sich \"uberlagernder Streumechanismen aufzustellen. Eine Modellinvertierung erlaubt dann die Bestimmung von Schichtdicken und anderer Parameter des Objekts, was sich z.B. zur Bestimmung von Waldh\"ohen und Bodentopographie ausnutzen l\"asst [31]. Kapitel 4 besch\"aftigt sich mit der Verarbeitung interferometrischer SAR Daten. In Abschnitt 4.1 werden wiederum zuerst die grundlegenden Konzepte von SAR Interferometrie und differentieller SAR Interferometrie vorgestellt. In der Folge wird auf die Besonderheiten von flugzeuggest\"utzter Repeat-Pass SAR Interferometrie eingegangen, eine wichtige Variante der Interferometrie, die aber bislang aufgrund verschiedener Fehlereinfl\"usse (siehe Abschnitt 4.2) nur sehr eingeschr\"ankt m\"oglich ist. In 4.3 werden mehrere Techniken zur Umgehung dieser Probleme eingef\"uhrt, wobei wiederum Zeit-Frequenz Analysen benutzt werden, um entweder erweiterte Beobachtungsm\"oglichkeiten zu erhalten oder genauere Korrekturen anbringen zu k\"onnen. Along-Track Interferometrie / MTI: Die im vorherigen Abschnitt beschriebene SAR Interferometrie wird pr\"azise auch als across-track Interferometrie bezeichnet. Des weiteren existiert auch noch eine zweite Variante, die sogenannte along-track Interferometrie (ATI). Bei ihr werden zwei oder mehr, in Flugrichtung versetzte, Antennenelemente simultan betrieben. Bewegt sich ein Objekt w\"ahrend der Aufnahme in Blickrichtung des Sensors, so kommt es durch die geringf\"ugig verschiedenen Empfangszeitpunkte zu einer Phasenverschiebung zwischen den beiden Aufnahmen, was sich ausnutzen l\"asst, um die Geschwindigkeit des Objekts zu bestimmen. Fr\"uhe Experimente in Richtung along-track Interferometrie fanden z.B. bereits in den 1980er Jahren mit einem modifizierten AIRSAR Sensor statt [74]; in der Folge wurde ATI verbreitet zur Messung von Str\"omungsgeschwindigkeiten von Wasseroberfl\"achen eingesetzt. \"Uber die Jahre entstanden mehrere Variationen dieses Konzepts, welche vor allem das Ziel hatten, durch Einf\"uhrung weiterer Empf\"angerkan\"ale die Genauigkeit der Geschwindigkeitmessung zu verbessern [22][98]. Mit den geplanten TerraSAR-X und RADARSAT-2 Sensoren wird auch erstmals operationelle Along-Track Interferometrie mit einem zivilen satellitengest\"utzten Sensor m\"oglich sein [179][137]. Eine weitere M\"oglichkeit von Sensoren mit mehreren simultanen betriebenen Antennenelementen in Azimut ist die Detektion von Position und Geschwindigkeit von Bewegtzielen am Boden (moving target detection, MTI) [184]. Die Anwendungsgebiete lagen bislang vor allem im milit \"arischen Bereich [46], in neuerer Zeit wird aber auch der Einsatz von MTI f\"ur die zivile Verkehrsbeobachtung vorgeschlagen [126][87]. Sind mehr als 2 Empf\"angerkan\"ale verf\"ugbar, wird zur Unterdr\"uckung der R\"uckstreuung nicht-bewegter Ziele bei MTI Anwendungen gerne auf sogenanntes space-time adaptive processing (STAP) zur\"uckgegriffen [101]. Diese Arbeit besch\"aftigt sich nicht weiter mit der Verarbeitung von Daten, die simultan von einem Antennenarray in Azimut aufgezeichnet wurden, die also simultan unter mehreren Squintwinkeln empfangen wurden. Zeit-Frequenz Analysen: Existiert nur ein Empf\"angerkanal, so l\"asst sich trotzdem eine gewisse Adaption auf den Squintwinkel \"uber sogenannte Zeit-Frequenz Analysen erreichen. Dabei wird das Doppler-Spektrum in Azimut in mehrere Subb\"ander aufgespalten, die jeweils eine leicht unterschiedliche mittlere Blickrichtung auf die Szene repr\"asentieren. Man erh\"alt damit gleichzeitig eine gewisse Aufl\"osung in Azimut (d.h. Zeit) als auch im Squintwinkel (d.h. Doppler-Frequenz). Gleiches ist auch in Entfernungsrichtung m\"oglich, wobei hier die verschiedenen Subb\"ander verschiedenen Wellenl\"angen entsprechen. Zeit-Frequenz Zerlegungen besitzen eine lange Geschichte in der SAR Fernerkundung und wurden vor allem zur optimierten Prozessierung von SAR Daten [129][190] und zur Analyse bzw. zur Fokussierung von bewegten Objekten verwendet [26]. In neuerer Zeit wurden ausserdem Zeit-Frequenzanalysen direkt in der SAR Bildanalyse eingesetzt. So l\"asst sich beispielsweise das Korrelationsverhalten zwischen Subaperturen ausnutzen, um koh\"arente Punktstreuer in der Szene zu detektieren [191][185]. Polarimetrische Signaturen weisen in vielen F\"allen eine starke Abh\"angigkeit vom Blickwinkel auf, was ein Problem f\"ur hochaufl\"osende SAR Systeme darstellt und durch polarimetrische Zeit-Frequenz Analysen gel\"ost werden kann [1][58]. Noch einen Schritt weiter geht die Kombination von Polarimetrie, Interferometrie und Zeit-Frequenzanalyse auf Basis von Waveletzerlegungen mit dem Ziel der optimalen Erzeugung von H\"ohenmodellen [37]. In dieser Arbeit wird an mehreren Stellen auf die Zeit-Frequenzanalyse von SAR Daten eingegangen. Kapitel 2.2.2 gibt eine Einf\"uhrung in der Bildung von Subaperturen mit Hilfe Fourier- Transformationen. In Abschnitt 2.3.2 und 2.3.3 wird eine Zeit-Frequenz Analyse teilprozessierter Daten verwendet, um Fehler der Bewegungskompensation in adaptiver Weise auszugleichen. In \"ahnlicher Weise wird in Kapitel 4.3.1 eine Zeit-Frequenz Analyse benutzt, um eine Adaption der Bewegungskompensation auf die Topographie der Szene zu erreichen. Kapitel 3.2 besch\"aftigt sich mit der Zeit-Frequenzanalyse polarimetrischer SAR Daten zur Eliminierung anisotroper R\"uckstreuung. Schliesslich wird in Kapitel 4.3.2 eine Zeit-Frequenz Analyse interferometrischer Daten vorgenommen, um kleinste Fehler in der Bestimmung der Basislinie aus den Daten selbst abzuleiten. Weitere Techniken: Die obige Aufstellung mehrkanaliger Erweiterungen des SAR Prinzips ist bei weitem nicht vollst\"andig und gibt nur einen \"Uberblick \"uber die wichtigsten Bereiche. Eine wichtige noch zu erw\"ahnende Technik ist die Bildung von Zeitreihen, d.h. die regelm\"assige Beobachtung eines Gebiets mit anschliessender kombinierter Auswertung der Datens\"atze. Dies l\"asst sich nat\"urlich in vielerlei Hinsicht direkt zur Beobachtung von zeitlich ver\"anderlichen Prozessen einsetzen. Aber auch im Sinne der differentiellen SAR Interferometrie werden solche Zeitreihen z.B. zur Filterung von atmosph\"arischen und topographischen Fehlern verwendet, was es erlaubt, minimalste Bodendeformationen sehr zuverl\"assig zu detektieren [47][48]. Eine andere M\"oglichkeit, einen solchen Datensatz mit vielen interferometrischen Basislinien kombiniert auszuwerten, stellt die sogenannte SAR Tomographie dar. Bei ihr wird eine zus\"atzliche synthetische Apertur senkrecht zu Azimut- und Entfernungsrichtung aufgebaut, um eine echte dreidimensionale Abbildung der Szene zu erreichen [168]. Dies Technik l\"asst sich wiederum auch mit der SAR Polarimetrie kombinieren [81]. Schwerpunkt dieser Arbeit wird die Verarbeitung multimodaler hochaufl\"osender SAR Daten bilden. Zu diesem Zweck wird ein Exkurs durch die drei aktuell wohl bedeutsamsten Themenkomplexe der SAR Fernerkundung unternommen - der SAR Prozessierung (Kapitel 2), der SAR Polarimetrie (Kapitel 3) und der SAR Interferometrie (Kapitel 4). Zus\"atzlich zu einer detaillierten Einf\"uhrung in das jeweilige Gebiet soll in allen Bereichen aufgezeigt werden, wie sich durch Hinzunahme multimodaler Verarbeitungstechniken, bzw. mit Hilfe der mehrkanaligen Information selbst, signifikante Verbesserungen in der Auswertung erzielen lassen. @MISC{ReigberHabil2008:MultimodalSAR, author = {Andreas Reigber}, title = {Multimodale Verarbeitung hochaufl\"osender SAR Daten}, month = {feb}, year = {2008}, note = {Habilitationsschrift an der Fakult\"at IV -Elektrotechnik un Informatik - der Technischen Universit\"at Berlin}, abstract = {Abbildende Radartechnik ist ein Fernerkundungsverfahren, welches das Ziel hat, von einer beobachteten Gegend eine hochaufgel\"oste Reflektivit\"atskarte im Mikrowellenbereich zu erzeugen. Erreicht wird dies durch Abstrahlung und Empfang von elektromagnetischer Strahlung im Mikrowellenbereich, typischerweise durch Sensoren, die auf Flugzeugen oder Satelliten montiert sind. Unter einer ganzen Reihe von Mikrowellensensoren hat sich in den letzten Jahren ein besonderes Interesse in Radar mit synthetischer Apertur (SAR) herausgebildet. Der Grund hierf\"ur ist, dass das SAR als einziger Mikrowellensensor eine fl\"achige Abbildung mit einer hohen r\"aumlichen Aufl\"osung, die durchaus mit der optischer Systeme vergleichbar ist, erm\"oglicht. Die Entwicklungsgeschichte des Radars mit synthetischer Apertur begann bereits vor \"uber 50 Jahren mit der Idee, die Doppler-Verschiebung des Radarsignals zu nutzen, um die Azimutaufl\"osung des damals aktuellen side-looking airborne radar (SLAR) zu verbessern [215]. Zur Prozessierung der Daten war man, bis in die 1970er Jahre hinein, auf die Verwendung optischer, holographischer Verfahren angewiesen; erst danach war man in der Lage, mittels digitaler Datenverarbeitung hochaufgel\"oste SAR Aufnahmen in hoher Qualit\"at zu erzeugen [10],[216]. Seitdem entwickelte sich die Fernerkundung mit SAR Sensoren rasant weiter, hin zu immer h\"oheren Aufl\"osungen und Aufnahmemodi. In den letzten 10 Jahren gewannen dabei vor allem die mehrkanalige SAR Modi stark an Bedeutung, wie z.B. multispektrales SAR [66], SAR Interferometrie [8] und SAR Polarimetrie [13]. Diese Arbeit besch\"aftigt sich vor allem mit speziellen Datenverarbeitungstechniken solcher mehrkanaliger SAR Daten. SAR Sensoren arbeiten im Mikrowellenbereich des elektromagnetischen Spektrums bei Wellenl\"angen zwischen wenigen Millimetern und mehreren Metern. Betrachtet man das Transmissionsspektrum der Erdatmosph\"are, so stellt man fest, dass bei Wellenl\"angen gr\"osser als etwa 1cm praktisch keine nennenswerte Absorption mehr auftritt. Dies gilt sowohl f\"ur die Luft selbst als auch f\"ur Wolken und kleinere Wassertropfen. SAR Aufnahmen lassen sich daher praktisch unabh\"angig von den aktuell herrschenden Wetterbedingungen generieren, wohingegen Wolken und Nebel f\"ur optische Systeme oft eine grosse Einschr\"ankung darstellen. Als aktives System, das seine eigene Beleuchtung mitbringt, besteht weiterhin keinerlei Abh\"angigkeit von der jeweiligen Tageszeit. Zusammengenommen f\"uhren diese Punkte dazu, dass sich SAR Sensoren besonders gut f\"ur verl\"assliche und regelm\"assige Beobachtungen eignen. Der Informationsgehalt von Radaraufnahmen ist deutlich anders gelagert als der von optischen oder Infrarotsystemen. W\"ahrend im optischen Bereich vor allem die molekulare Zusammensetzung des Objekts f\"ur die charakteristische Reflektivit\"at des Objekts verantwortlich zeichnet, sind im Mikrowellenbereich vor allem die geometrische Form sowie die dielektrischen Eigenschaften f\"ur die St\"arke der R\"uckstreuung von Bedeutung. In Radaraufnahmen tritt daher das Relief und morphologische Strukturen besonders deutlich hervor. Auch \"Anderungen in der Leitf\"ahigkeit, z.B. durch unterschiedliche Bodenfeuchte, k\"onnen so beobachtet werden. Aufgrund der Sensitivit \"at auf dielektrische Eigenschaften k\"onnen im Prinzip sogar Informationen \"uber den Vegetationszustand gesammelt werden. Eine weitere wichtige Eigenschaft von Radaraufnahmen ergibt sich aus den Ausbreitungseigenschaften von Mikrowellen: Durch ihre lange Wellenl\"ange sind Mikrowellen bis zu einem gewissen Grad in der Lage, in Vegetationsschichten, in Schnee und Eis und sogar in den Boden einzudringen [203]. Das Eindringverm\"ogen h\"angt dabei von der Wellenl\"ange des Sensors, aber auch von den dielektrischen Eigenschaften und der Leitf\"ahigkeit des Objekts ab. K\"urzere Wellenl\"angen, wie das X-Band, werden stark ged\"ampft und daher vor allem von der Oberfl\"ache reflektiert. In k\"urzeren Wellenl\"angen sammelt man daher in erster Linie Informationen \"uber die oberen Schichten von Vegetation oder Boden. L\"angere Wellenl\"angen, wie L- oder P-Band, dringen hingegen oft tief in Vegetation ein. R\"uckstreuung in solchen Wellenl\"angen enthalten daher Anteile aus dem gesamten r\"uckstreuenden Volumen. An dieser Stelle zeigt sich bereits ein typisches Problem der Fernerkundung im allgemeinen: Die zu untersuchenden Objekte sind meist recht komplex, und ihre Eigenschaften wirken sich in vielerlei Weise auf das gemessene Bildergebnis aus. Ein Fernerkundungssensor liefert aber nur einen sehr niedrigdimensionalen Raum von Observablen, im Falle eines konventionellen SAR Sensors sogar nur einen einzigen Messwert. Es ist daher in vielen F\"allen sehr schwierig, oder sogar unm\"oglich, aus dem gemessenen Bildergebnis auf den gesuchten Objektparameter zu schliessen. Es besteht also ein Mehrdeutigkeitsproblem: Mehrere verschiedene S\"atze von Objektparametern k\"onnen zu exakt dem gleichem Satz an Observablen f\"uhren. Der einzige Weg dieses Problem zu umgehen, ist die Erh\"ohung der Dimensionalit\"at des Sensors, also die Verwendung mehrerer unabh\"angiger Empfangskan\"ale. Thema dieser Arbeit sind spezielle sogenannte multimodale Verarbeitungstechniken, die f\"ur die korrekte Bearbeitung solcher multidimensionaler Datens\"atze notwendig sind. Es soll dabei insbesondere aufgezeigt werden, dass durch Hinzunahme weiterer Datendimensionen generell eine verbesserte Informationsextraktion erreicht, bzw. mit ihnen eine verbesserte Datenverarbeitung erzielt werden kann. Generell ergeben sich in der SAR Fernerkundung vor allem folgende M\"oglichkeiten f\"ur multimodale Erweiterungen: Multifrequentes SAR: Alle bislang betriebenen satellitengest\"utzten SAR Systeme arbeiten nur in einem einzigen Band, besitzen also eine dedizierte zentrale Wellenl\"ange. Verwendet wird dabei meist das C-Band, wie z.B. bei den europ\"aischen ERS-1, ERS-2 [4] und ENVISAT [119] und den kanadischen RADARSAT-1 [161] und RADARSAT-2 [125]. Es kommt aber auch L-Band, z.B. beim japanischen ALOS-PALSAR [99], und X-Band, wie bei in K\"urze startenden TerraSAR-X [214], zum Einsatz. Prinzipiell stehen daher also SAR Daten in verschiedenen Wellenl\"angen zur Verf\"ugung. Trotzdem sind solche inhomogenen Datenquellen als nicht ideal anzusehen, da unterschiedliche Aufnahmezeitpunkte, sowie abweichende Bildaufl\"osungen und Sensorcharakteristika zu beachten sind. Die einzige Ausnahme stellen die Shuttle Missionen SIR-C/X-SAR im Jahr 1994 (X-, C- und L-Band) [92] und SRTM im Jahr 2000 (X- und C-Band) [213] dar, bei denen zum ersten Mal aus dem Orbit multifrequente SAR Daten simultan aufgezeichnet wurden. Im Gegensatz dazu bieten die allermeisten heutzutage betriebenen flugzeuggest\"utzten SAR Systeme die M\"oglichkeit mehrerer Wellenl\"angen. Zu nennen sind hier beispielsweise das E-SAR System des Deutschen Zentrums f\"ur Luft- und Raumfahrt (X-, C-, S-, L- und P-Band) [89], das franz\"osische RAMSES System von Onera (W-, Ka-, Ku-, X-, C-, S-, L- und P-Band) [45] oder das amerikanische AIRSAR System des JPLs (X-, C- und L-Band) [207]. Die Reflektivit\"at im Mikrowellenbereich kann stark von der verwendeten Wellenl\"ange abh\"angen, da die Dielektrizit\"atskonstante vieler Materialien stark frequenzabh\"angig ist [203]. Auch die Oberfl\"achenrauhigkeit hat in verschiedenen Wellenl\"angen einen unterschiedlichen Einfluss auf die St\"arke der R\"uckstreuung [203]. Aus diesen Gr\"unden erscheinen SAR Aufnahmen, die in unterschiedlichen B\"andern angefertigt worden sind, oft sehr verschieden. Genau diese Unterschiede erlauben es mache Oberfl\"achen oder Materialien zu trennen, die bei Betrachtung in nur einer Wellenl\"ange noch identisch erscheinen; dies l\"asst sich z.B. zu Klassifikationszwecken ausnutzen. Wie bereits zuvor erw\"ahnt, \"andert sich mit der Wellenl\"ange auch das Eindringverm\"ogen der Mikrowellen. Es wird in verschiedenen B\"andern also auch Informationen aus unterschiedlichen Schichten eines Volumens gewonnen; dies kann dazu benutzt werden um beispielsweise in Kombination mit interferometrischen Ans\"atzen Vegetationsh\"ohen zu bestimmen [217][205]. Dadurch dass sich die verschiedenen B\"ander im allgemeinen nicht spektral \"uberlappen, sind multifrequente SAR Daten untereinander inkoh\"arent. Die Datenverarbeitung der einzelnen Kan\"ale erfolgt daher in erster Linie unabh\"angig voneinander; erst zum Schluss werden die verschiedenen Aufnahmen kombiniert ausgewertet. In dieser Arbeit wird aus diesem Grund nicht weiter auf die Verarbeitung multifrequenter Daten eingegangen. Polarimetrisches SAR: Die SAR Polarimetrie (PolSAR) ist eine weitere wichtige M\"oglichkeit, den Beobachtungsraum von SAR Sensoren zu erweitern. Elektromagnetische Wellen sind transversaler Natur und erlauben daher zwei orthogonale Schwingungsrichtungen. Dies gilt sowohl f\"ur den Sende- als auch f\"ur den Empfangskanal, man erh\"alt also im Idealfall 4 unabh\"angige Messungen. Dies ist Gegenstand der Radarpolarimetrie, initiiert im Jahre 1948 durch G.W. Sinclair mit der Einf\"uhrung des Konzepts der Streumatrizen [188]. Da Radarpolarimetrie deutlich h\"ohere Hardwareanforderungen stellt, blieb sie lange nur ein theoretisches Konstrukt [90] [12], und ihr praktischer Nutzen wurde vor allem im zivilen Bereich lange nicht erkannt. Diese Situation \"anderte sich mit der Verf\"ugbarkeit polarimetrischer SAR Daten verschiedener flugzeuggest \"utzter SAR Systeme, wie beispielsweise dem AIRSAR oder dem E-SAR, sowie den beiden SIR-C/X-SAR Missionen, bei denen polarimetrische SAR Daten in mehreren Wellenl\"angen erzeugt wurden. Seitdem hat sich die SAR Polarimetrie zu einer etablierten Fernerkundungsmethode entwickelt, welche auch in zunehmenden Masse von den neuesten SAR Satelliten, wie dem kanadischen RADARSAT-2, dem japanischen ALOS-PALSAR und dem deutschen TerraSAR-X, unterst\"utzt wird. Eine besondere Eigenschaft der SAR Polarimetrie ist die prinzipielle M\"oglichkeit, verschiedenartige R\"uckstreumechanismen unterscheiden zu k\"onnen. Dies kann erreicht werden, da die gemessenen polarimetrischen Signaturen stark vom jeweils aufgetretenen Streuprozess abh\"angen. Im Vergleich zum herk\"ommlichen einkanaligen SAR ergibt sich damit eine signifikante Verbesserung bei der Unterscheidung verschiedener Oberfl\"achentypen, was sich beispielsweise in der Verbesserung von Landnutzungsklassifikationen [35],[111] ausn\"utzen l\"asst. Des weiteren erlaubt die SAR Polarimetrie durch ihren vergr\"osserten Raum an Observablen auch einfache physikalische Modellierungen. Durch Invertierung polarimetrischer Streumodelle lassen sich z.B. Bodenparameter wie Rauigkeit und Bodenfeuchte bestimmen [30]. Weiterhin lassen sich mit Hilfe der SAR Polarimetrie auch die Anteile verschiedener charakteristischer R\"uckstreuklassen ermitteln [65], selbst wenn sie sich innerhalb eines Pixels gegenseitig \"uberlagern. In Kapitel 3 wird auf die Besonderheiten der Verarbeitung polarimetrischer SAR Daten eingegangen. Aufbauend auf die grundlegenden Konzepte der SAR Polarimetrie, zusammengefasst in Abschnitt 3.1, wird in Abschnitt 3.2 eine Zeit-Frequenz Analyse polarimetrischer Daten vorgenommen. Der hierdurch weiter vergr\"osserter Raum an Observablen erlaubt die Detektion st\"orender anisotroper R\"uckstreumechanismen sowie die Entfernung ihres Einflusses aus den Daten. Des weiteren wird in Abschnitt 3.1.2 ein verbessertes polarimetrisches Klassifikationsverfahren unter Verwendung von Nachbarschaftsinformation als zus\"atzlicher Datendimension abgeleitet. Interferometrisches SAR: SAR Interferometrie (InSAR) ist eine multimodale Erweiterung in der SAR Fernerkundung, welche den Beobachtungsraum geometrisch durch mehrere Aufnahmen von leicht verschiedenen Orten erweitert. Anschaulich wird in der SAR Interferometrie eine leichte Variation des Einfallswinkels vorgenommen, wobei davon ausgegangen wird, dass sich die R\"uckstreueigenschaften dabei nicht signifikant ver\"andern. Analysiert wird dann der aufgetretene Phasenunterschied zwischen zwei oder mehreren solcher Aufnahmen, der einen direkten Zusammenhang zu der Topographie des Bodens aufweist und sich daher zur Erstellung von genauen H\"ohenmodellen eignet. Die ersten Experimente in diese Richtung wurden 1974 von L.C. Graham durchgef\"uhrt [79] und in den 1980ern experimentell in Form von InSAR Modifikationen am AIRSAR Sensor fortgef\"uhrt [220]. Popul\"ar wurde die SAR Interferometrie aber erst mit dem Start der ERS Satelliten, die erstmals operationelle satellitengest\"utzte SAR Interferometrie bieten konnten. Im Jahr 2000 kumulierte diese Entwicklung in der Shuttle Radar Topography Mission (SRTM), w\"ahrend der ein hochgenaues H\"ohenmodell der gesamten Landoberfl\"ache der Erde zwischen 60 deg N und 60 deg S erzeugt wurde [213]. Die SAR Interferometrie ist heutzutage eine etablierte Technik, welche mit einer Vielzahl von satellitengest\"utzten Sensoren m\"oglich ist [68][72][128]. Neben der Abbildung der Terraintopographie kann die SAR Interferometrie auch zur Bestimmung kleinster Topographie\"anderungen eingesetzt werden. Mit dieser sogenannten differentiellen SAR Interferometrie (DInSAR) lassen sich durch Phasenmessung Genauigkeiten unterhalb der Wellenl\"ange, also typischerweise bis in den Millimeterbereich hinein, erzielen. Dies ist in verschiedensten Anwendungsbereichen einsetzbar, wie z.B. in der Analyse tektonischer Prozesse, oder in der Beobachtung von Absenkungsprozessen als Folge menschlicher Bergbauaktivit\"aten [124],[48],[105]. Des weiteren l\"asst sich der erweiterte Beobachtungsraum der SAR Interferometrie auch mit dem der SAR Polarimetrie verschneiden [142]. In der sogenannten polarimetrischen SAR Interferometrie (PolInSAR) wird dies ausgenutzt, um physikalische R\"uckstreumodelle mehrerer sich \"uberlagernder Streumechanismen aufzustellen. Eine Modellinvertierung erlaubt dann die Bestimmung von Schichtdicken und anderer Parameter des Objekts, was sich z.B. zur Bestimmung von Waldh\"ohen und Bodentopographie ausnutzen l\"asst [31]. Kapitel 4 besch\"aftigt sich mit der Verarbeitung interferometrischer SAR Daten. In Abschnitt 4.1 werden wiederum zuerst die grundlegenden Konzepte von SAR Interferometrie und differentieller SAR Interferometrie vorgestellt. In der Folge wird auf die Besonderheiten von flugzeuggest\"utzter Repeat-Pass SAR Interferometrie eingegangen, eine wichtige Variante der Interferometrie, die aber bislang aufgrund verschiedener Fehlereinfl\"usse (siehe Abschnitt 4.2) nur sehr eingeschr\"ankt m\"oglich ist. In 4.3 werden mehrere Techniken zur Umgehung dieser Probleme eingef\"uhrt, wobei wiederum Zeit-Frequenz Analysen benutzt werden, um entweder erweiterte Beobachtungsm\"oglichkeiten zu erhalten oder genauere Korrekturen anbringen zu k\"onnen. Along-Track Interferometrie / MTI: Die im vorherigen Abschnitt beschriebene SAR Interferometrie wird pr\"azise auch als across-track Interferometrie bezeichnet. Des weiteren existiert auch noch eine zweite Variante, die sogenannte along-track Interferometrie (ATI). Bei ihr werden zwei oder mehr, in Flugrichtung versetzte, Antennenelemente simultan betrieben. Bewegt sich ein Objekt w\"ahrend der Aufnahme in Blickrichtung des Sensors, so kommt es durch die geringf\"ugig verschiedenen Empfangszeitpunkte zu einer Phasenverschiebung zwischen den beiden Aufnahmen, was sich ausnutzen l\"asst, um die Geschwindigkeit des Objekts zu bestimmen. Fr\"uhe Experimente in Richtung along-track Interferometrie fanden z.B. bereits in den 1980er Jahren mit einem modifizierten AIRSAR Sensor statt [74]; in der Folge wurde ATI verbreitet zur Messung von Str\"omungsgeschwindigkeiten von Wasseroberfl\"achen eingesetzt. \"Uber die Jahre entstanden mehrere Variationen dieses Konzepts, welche vor allem das Ziel hatten, durch Einf\"uhrung weiterer Empf\"angerkan\"ale die Genauigkeit der Geschwindigkeitmessung zu verbessern [22][98]. Mit den geplanten TerraSAR-X und RADARSAT-2 Sensoren wird auch erstmals operationelle Along-Track Interferometrie mit einem zivilen satellitengest\"utzten Sensor m\"oglich sein [179][137]. Eine weitere M\"oglichkeit von Sensoren mit mehreren simultanen betriebenen Antennenelementen in Azimut ist die Detektion von Position und Geschwindigkeit von Bewegtzielen am Boden (moving target detection, MTI) [184]. Die Anwendungsgebiete lagen bislang vor allem im milit \"arischen Bereich [46], in neuerer Zeit wird aber auch der Einsatz von MTI f\"ur die zivile Verkehrsbeobachtung vorgeschlagen [126][87]. Sind mehr als 2 Empf\"angerkan\"ale verf\"ugbar, wird zur Unterdr\"uckung der R\"uckstreuung nicht-bewegter Ziele bei MTI Anwendungen gerne auf sogenanntes space-time adaptive processing (STAP) zur\"uckgegriffen [101]. Diese Arbeit besch\"aftigt sich nicht weiter mit der Verarbeitung von Daten, die simultan von einem Antennenarray in Azimut aufgezeichnet wurden, die also simultan unter mehreren Squintwinkeln empfangen wurden. Zeit-Frequenz Analysen: Existiert nur ein Empf\"angerkanal, so l\"asst sich trotzdem eine gewisse Adaption auf den Squintwinkel \"uber sogenannte Zeit-Frequenz Analysen erreichen. Dabei wird das Doppler-Spektrum in Azimut in mehrere Subb\"ander aufgespalten, die jeweils eine leicht unterschiedliche mittlere Blickrichtung auf die Szene repr\"asentieren. Man erh\"alt damit gleichzeitig eine gewisse Aufl\"osung in Azimut (d.h. Zeit) als auch im Squintwinkel (d.h. Doppler-Frequenz). Gleiches ist auch in Entfernungsrichtung m\"oglich, wobei hier die verschiedenen Subb\"ander verschiedenen Wellenl\"angen entsprechen. Zeit-Frequenz Zerlegungen besitzen eine lange Geschichte in der SAR Fernerkundung und wurden vor allem zur optimierten Prozessierung von SAR Daten [129][190] und zur Analyse bzw. zur Fokussierung von bewegten Objekten verwendet [26]. In neuerer Zeit wurden ausserdem Zeit-Frequenzanalysen direkt in der SAR Bildanalyse eingesetzt. So l\"asst sich beispielsweise das Korrelationsverhalten zwischen Subaperturen ausnutzen, um koh\"arente Punktstreuer in der Szene zu detektieren [191][185]. Polarimetrische Signaturen weisen in vielen F\"allen eine starke Abh\"angigkeit vom Blickwinkel auf, was ein Problem f\"ur hochaufl\"osende SAR Systeme darstellt und durch polarimetrische Zeit-Frequenz Analysen gel\"ost werden kann [1][58]. Noch einen Schritt weiter geht die Kombination von Polarimetrie, Interferometrie und Zeit-Frequenzanalyse auf Basis von Waveletzerlegungen mit dem Ziel der optimalen Erzeugung von H\"ohenmodellen [37]. In dieser Arbeit wird an mehreren Stellen auf die Zeit-Frequenzanalyse von SAR Daten eingegangen. Kapitel 2.2.2 gibt eine Einf\"uhrung in der Bildung von Subaperturen mit Hilfe Fourier- Transformationen. In Abschnitt 2.3.2 und 2.3.3 wird eine Zeit-Frequenz Analyse teilprozessierter Daten verwendet, um Fehler der Bewegungskompensation in adaptiver Weise auszugleichen. In \"ahnlicher Weise wird in Kapitel 4.3.1 eine Zeit-Frequenz Analyse benutzt, um eine Adaption der Bewegungskompensation auf die Topographie der Szene zu erreichen. Kapitel 3.2 besch\"aftigt sich mit der Zeit-Frequenzanalyse polarimetrischer SAR Daten zur Eliminierung anisotroper R\"uckstreuung. Schliesslich wird in Kapitel 4.3.2 eine Zeit-Frequenz Analyse interferometrischer Daten vorgenommen, um kleinste Fehler in der Bestimmung der Basislinie aus den Daten selbst abzuleiten. Weitere Techniken: Die obige Aufstellung mehrkanaliger Erweiterungen des SAR Prinzips ist bei weitem nicht vollst\"andig und gibt nur einen \"Uberblick \"uber die wichtigsten Bereiche. Eine wichtige noch zu erw\"ahnende Technik ist die Bildung von Zeitreihen, d.h. die regelm\"assige Beobachtung eines Gebiets mit anschliessender kombinierter Auswertung der Datens\"atze. Dies l\"asst sich nat\"urlich in vielerlei Hinsicht direkt zur Beobachtung von zeitlich ver\"anderlichen Prozessen einsetzen. Aber auch im Sinne der differentiellen SAR Interferometrie werden solche Zeitreihen z.B. zur Filterung von atmosph\"arischen und topographischen Fehlern verwendet, was es erlaubt, minimalste Bodendeformationen sehr zuverl\"assig zu detektieren [47][48]. Eine andere M\"oglichkeit, einen solchen Datensatz mit vielen interferometrischen Basislinien kombiniert auszuwerten, stellt die sogenannte SAR Tomographie dar. Bei ihr wird eine zus\"atzliche synthetische Apertur senkrecht zu Azimut- und Entfernungsrichtung aufgebaut, um eine echte dreidimensionale Abbildung der Szene zu erreichen [168]. Dies Technik l\"asst sich wiederum auch mit der SAR Polarimetrie kombinieren [81]. Schwerpunkt dieser Arbeit wird die Verarbeitung multimodaler hochaufl\"osender SAR Daten bilden. Zu diesem Zweck wird ein Exkurs durch die drei aktuell wohl bedeutsamsten Themenkomplexe der SAR Fernerkundung unternommen - der SAR Prozessierung (Kapitel 2), der SAR Polarimetrie (Kapitel 3) und der SAR Interferometrie (Kapitel 4). Zus\"atzlich zu einer detaillierten Einf\"uhrung in das jeweilige Gebiet soll in allen Bereichen aufgezeigt werden, wie sich durch Hinzunahme multimodaler Verarbeitungstechniken, bzw. mit Hilfe der mehrkanaligen Information selbst, signifikante Verbesserungen in der Auswertung erzielen lassen.}, address = {Technische Universit\"at Berlin}, keywords = {SAR Processing, airborne SAR, omega-k, Range Migration Algorithm, Wave Number Domain Algorithm, Extended Chirp Scaling, ECS, SAR Interferometry, Interferometry, InSAR, Residual Motion Errors, Residual Errors, Motion Compensation, MoComp, PolInSAR, Polarimetry}, owner = {ofrey}, pdf = {http://www.geo.uzh.ch/~ofrey/protected/PAPERS/ReigberHabil2008.pdf}, url = {http://elib.dlr.de/54771/01/reigber_habil.pdf} }
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Last modified: Wed Sep 8 19:32:46 2010
Author: Othmar Frey , Remote Sensing Laboratories (RSL), University of Zurich, Switzerland .
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