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SSG Seminar Abstract

Anisotropy Characterization in Synthetic Aperture Radar using Sparse Signal Representation

Kush Varshney

We consider the problem of jointly forming images and characterizing anisotropy from wide-angle synthetic aperture radar (SAR) measurements.  Conventional SAR image formation techniques assume isotropic scattering, which is not valid with wide-angle apertures.  We present a method based on a sparse representation of aspect-dependent scattering with an overcomplete basis composed of basis vectors with varying levels of angular persistence.  Solved as an inverse problem, the result is a complex-valued, aspect-dependent response for each spatial location in a scene.  Our non-parametric approach considers all point scatterers in a scene jointly.  The choice of the overcomplete basis set incorporates prior knowledge of aspect-dependent scattering, but the method is flexible enough to admit solutions that may not match a family of parametric functions.  We enforce sparsity through regularization based on the lp quasi-norm, p<1.  This formulation leads to an optimization problem that is solved through robust half-quadratic methods.  We also develop a graph-structured interpretation of the overcomplete basis leading towards approximate algorithms using hill-climbing search with appropriate stopping conditions and search heuristics.  We present experimental results on synthetic scenes and on realistic radar measurements of a man-made vehicle.

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