Tomographic SAR Inversion by L-1-Norm Regularization-The Compressive Sensing Approach

作者：Zhu Xiao Xiang^*; Bamler Richard

来源：IEEE Transactions on Geoscience and Remote Sensing, 2010, 48(10): 3839-3846.

DOI：10.1109/TGRS.2010.2048117

• Compressive sensing (CS)
• differential synthetic aperture radar tomography (D-TomoSAR)
• TerraSAR-X
• urban mapping

Synthetic aperture radar (SAR) tomography (TomoSAR) extends the synthetic aperture principle into the elevation direction for 3-D imaging. The resolution in the elevation direction depends on the size of the elevation aperture, i.e., on the spread of orbit tracks. Since the orbits of modern meter-resolution spaceborne SAR systems, like TerraSAR-X, are tightly controlled, the tomographic elevation resolution is at least an order of magnitude lower than in range and azimuth. Hence, super-resolution reconstruction algorithms are desired. The high anisotropy of the 3-D tomographic resolution element renders the signals sparse in the elevation direction; only a few pointlike reflections are expected per azimuth-range cell. This property suggests using compressive sensing (CS) methods for tomographic reconstruction. This paper presents the theory of 4-D (differential, i.e., space-time) CS TomoSAR and compares it with parametric (nonlinear least squares) and nonparametric (singular value decomposition) reconstruction methods. Super-resolution properties and point localization accuracies are demonstrated using simulations and real data. A CS reconstruction of a building complex from TerraSAR-X spotlight data is presented.

• 出版日期2010-10