Indoor scene reconstruction for through-the-wall radar imaging using low-rank and sparsity constraints

Authors

Van H. Tang, University of WollongongFollow
Abdesselam Bouzerdoum, University of WollongongFollow
Son Lam Phung, University of WollongongFollow
Fok Hing Chi Tivive, University of WollongongFollow

RIS ID

108648

Publication Details

V. H. Tang, A. Bouzerdoum, S. L. Phung & F. H. C. Tivive , "Indoor scene reconstruction for through-the-wall radar imaging using low-rank and sparsity constraints," in 2016 IEEE Radar Conference (RadarConf), 2016, pp. 1-4.

Abstract

This paper addresses the problem of indoor scene reconstruction in compressed sensing through-the-wall radar imaging. The proposed method is motivated by two observations that wall reflections reside in a low-rank subspace and the imaged scene tends to be sparse. The task of mitigating the wall reflections and reconstructing an image of the scene behind-the-wall is cast as a joint low-rank and sparsity constrained optimization problem, where a low-rank matrix captures the wall returns and a sparse matrix represents the formed image. An iterative algorithm is developed to estimate the low-rank matrix and the sparse scene vector from a reduced measurement set. Experimental results using real radar data show that the proposed model is very effective at reconstructing the indoor image and removing wall clutter.