Through-the-wall radar imaging using a distributed Quasi-Newton method

Abstract

This paper considers a distributed network of through-the-wall imaging radars and provides a solution for accurate indoor scene reconstruction in the presence of multipath propagation. A sparsity-based method is proposed for eliminating ghost targets under imperfect knowledge of interior wall locations. Instead of aggregating and processing the observations at a central fusion station, joint scene reconstruction and estimation of interior wall locations is carried out in a distributed manner across the network. Using alternating minimization approach, the sparse scene is reconstructed using the recently proposed MDOMP algorithm, while the wall location estimates are obtained with a distributed quasi-Newton method (D-QN) proposed in this paper. The efficacy of the proposed approach is demonstrated using numerical simulation.