Sparse Fusion Imaging for Subaperture Through-wall Radar System

摘要

This paper formulates and solves a problem of multi-subaperture through wall radar imaging (TWRI). The multi-subaperture is formed by using multiple short arrays. Firstly, by treating the imaging results corresponding to each subaperture as individual solutions, the multiple-subaperture TWRI problem is modeled as a joint sparse representation problem. Then, by exploiting the common sparsity property of target pixels over all subaperture channels, we propose a novel sparse fusion imaging method extended from the multitask Bayesian compressive sensing (MT-BCS). Simulated and experimental results demonstrate that the proposed method can detect and locate stationary targets behind the wall effectively.