TY - GEN
T1 - Radar Stationary and Moving Indoor Target Localization with Low-rank and Sparse Regularizations
AU - Tang, Van Ha
AU - Bouzerdoum, Abdesselam
AU - Phung, Son Lam
N1 - Publisher Copyright:
© 2019 IEEE.
PY - 2019/5
Y1 - 2019/5
N2 - This paper proposes a low-rank and sparse regularized optimization model to address the problem of wall clutter mitigation, stationary, and moving target indications using through-wall radar. The task of wall clutter suppression and target image reconstruction is formulated as a nuclear and {ell -1} penalized least squares optimization problem in which the nuclear-norm term enforces for a low-rank wall clutter matrix and the {ell -1} -norm term promotes the sparsity of the target images. An iterative algorithm based on the proximal gradient technique is introduced to solve the optimization problem. The solution comprises the wall clutter and images of stationary and moving targets. Experiments are conducted on real radar data under compressive sensing scenarios. The results show that the proposed model is very effective at removing unwanted wall clutter, reconstructing stationary targets, and capturing moving targets.
AB - This paper proposes a low-rank and sparse regularized optimization model to address the problem of wall clutter mitigation, stationary, and moving target indications using through-wall radar. The task of wall clutter suppression and target image reconstruction is formulated as a nuclear and {ell -1} penalized least squares optimization problem in which the nuclear-norm term enforces for a low-rank wall clutter matrix and the {ell -1} -norm term promotes the sparsity of the target images. An iterative algorithm based on the proximal gradient technique is introduced to solve the optimization problem. The solution comprises the wall clutter and images of stationary and moving targets. Experiments are conducted on real radar data under compressive sensing scenarios. The results show that the proposed model is very effective at removing unwanted wall clutter, reconstructing stationary targets, and capturing moving targets.
KW - Through-the-wall radar imaging
KW - compressive sensing.
KW - moving target indication
KW - wall clutter mitigation
UR - http://www.scopus.com/inward/record.url?scp=85069002545&partnerID=8YFLogxK
U2 - 10.1109/ICASSP.2019.8682438
DO - 10.1109/ICASSP.2019.8682438
M3 - Conference contribution
AN - SCOPUS:85069002545
T3 - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
SP - 2172
EP - 2176
BT - 2019 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2019 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 44th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2019
Y2 - 12 May 2019 through 17 May 2019
ER -