Tomographic synthetic aperture radar (SAR) imaging has been recently formulated in a wavelet-based compressed sensing (CS) framework. This paper reviews the underlying sparsity-driven algorithms for single-channel as well as polarimetric tomography, and discusses its applicability in terms of ambiguity rejection, physical validity, acquisition geometry, and required a priori knowledge. In addition, we present a comparison with traditional nonparametric spectral estimators by using L-band data acquired by the Experimental SAR (E-SAR) sensor of the German Aerospace Center (DLR).
Wavelet-Based Compressed Sensing for Polarimetric SAR Tomography
2013 ; Frascati, Italy
2013-01-30
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
Wavelet-Based Compressed Sensing for Polarimetric SAR Tomography
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