Two-Level Block Matching Pursuit for Polarimetric Through-Wall Radar Imaging

In this paper, we propose a two-level block matching pursuit (TLBMP) algorithm based on a probabilistic graph model for polarimetric through-wall radar imaging (TWRI). In typical L-band to X-band TWRI, indoor targets assume a spatial extent and occupy clustered pixels. When polarimetric sensing is used to obtain independent observations, radar images of clustered targets can be enhanced within the joint sparsity framework. Toward this objective, TLBMP is devised to exploit both the clustered property and the joint sparsity pattern of multiple polarimetric through-wall radar images. Simulations and experimental results based on polarimetric through-wall radar data demonstrate that compared to commonly used algorithms for solving the same underlying problem, TLBMP provides more informative imaging with higher target-to-clutter ratio.