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


During 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 issues will be solid as inverse scattering involving few targets and, therefore, benefit from CS and sparse reconstruction techniques. In specific, recognizing that the majority indoor targets are spatially extended, we have a tendency to exploit the clustering property of the sparse scene to realize enhanced imaging capability. Additionally, multiple polarization sensing modalities are used to get increased observation dimensionality within the group sparsity framework. The recently developed cluster multitask Bayesian CS approach is changed to effectively solve the formulated cluster and clustered sparse downside. Experimental results are presented to demonstrate the superiority of the proposed approach.

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