Skip to main content
placeholder image

Wall clutter mitigation using HOSVD in through-the-wall radar imaging with compressed sensing

Conference Paper


Download full-text (Open Access)

Abstract


  • This paper addresses the problem of wall clutter mitigation in through-the-wall radar imaging using compressed sensing. In the proposed method, the radar signals are recovered using a joint Bayesian sparse representation, and the estimated coefficients are transformed into a third-order data tensor. Then, higher-order singular value decomposition (HOSVD) is applied to form a multilinear wall subspace. To remove the returns associated with wall clutter, the radar signal is projected onto the complement of the wall subspace. Furthermore, a compact image formation model is developed using principal component analysis (PCA), which yields a smaller dictionary size and reduced noise. Experimental results show that the proposed HOSVD-based method outperforms the standard SVD-based wall clutter mitigation technique.

Publication Date


  • 2015

Citation


  • A. Bouzerdoum & F. Hing Chi. Tivive , "Wall clutter mitigation using HOSVD in through-the-wall radar imaging with compressed sensing," in IEEE International Conference on Digital Signal Processing (DSP), 2015, pp. 85-89.

Scopus Eid


  • 2-s2.0-84961367641

Ro Full-text Url


  • http://ro.uow.edu.au/cgi/viewcontent.cgi?article=5741&context=eispapers

Ro Metadata Url


  • http://ro.uow.edu.au/eispapers/4720

Start Page


  • 85

End Page


  • 89

Abstract


  • This paper addresses the problem of wall clutter mitigation in through-the-wall radar imaging using compressed sensing. In the proposed method, the radar signals are recovered using a joint Bayesian sparse representation, and the estimated coefficients are transformed into a third-order data tensor. Then, higher-order singular value decomposition (HOSVD) is applied to form a multilinear wall subspace. To remove the returns associated with wall clutter, the radar signal is projected onto the complement of the wall subspace. Furthermore, a compact image formation model is developed using principal component analysis (PCA), which yields a smaller dictionary size and reduced noise. Experimental results show that the proposed HOSVD-based method outperforms the standard SVD-based wall clutter mitigation technique.

Publication Date


  • 2015

Citation


  • A. Bouzerdoum & F. Hing Chi. Tivive , "Wall clutter mitigation using HOSVD in through-the-wall radar imaging with compressed sensing," in IEEE International Conference on Digital Signal Processing (DSP), 2015, pp. 85-89.

Scopus Eid


  • 2-s2.0-84961367641

Ro Full-text Url


  • http://ro.uow.edu.au/cgi/viewcontent.cgi?article=5741&context=eispapers

Ro Metadata Url


  • http://ro.uow.edu.au/eispapers/4720

Start Page


  • 85

End Page


  • 89