Compressive-Sensing-Based High-Resolution Polarimetric Through-the-Wall Radar Imaging Exploiting Target Characteristics

Abstract

In this letter, we consider high-resolution through-the-wall radar imaging (TWRI) using compressive sensing (CS) techniques that exploit the target and sensing characteristics. Many TWRI problems can be cast as inverse scattering involving few targets and, thus, benefit from CS and sparse reconstruction techniques. In particular, recognizing that most indoor targets are spatially extended, we exploit the clustering property of the sparse scene to achieve enhanced imaging capability. In addition, multiple polarization sensing modalities are used to obtain increased observation dimensionality within the group sparsity framework. The recently developed cluster multitask Bayesian CS approach is modified to effectively solve the formulated group and clustered sparse problem. Experimental results are presented to demonstrate the superiority of the proposed approach.