Van Ha, T. and Bouterdoum, A. and Phung, S.L. (2018) A Matrix Completion Approach for Wall-Clutter Mitigation in Compressive Radar Imaging of Indoor Targets. In: 2018 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2018, 15 April 2018 through 20 April 2018.
Wall clutter mitigation for radar imaging of indoor targets_ A matrix completion approach..pdf
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Abstract
This paper presents a low-rank matrix completion approach to tackle the problem of wall clutter mitigation for through-wall radar imaging in the compressive sensing context. In particular, the task of wall clutter removal is reformulated as a matrix completion problem in which a low-rank matrix containing wall clutter is reconstructed from compressive measurements. The proposed model regularizes the low-rank prior of the wall-clutter matrix via the nuclear norm, casting the wall-clutter mitigation task as a nuclear-norm penalized least squares problem. To solve this optimization problem, an iterative algorithm based on the proximal gradient technique is introduced. Experiments on simulated full-wave electromagnetic data are conducted under compressive sensing scenarios. The results show that the proposed matrix completion approach is very effective at suppressing unwanted wall clutter and enhancing the targets. © 2018 IEEE.
Item Type: | Conference or Workshop Item (Paper) |
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Divisions: | Faculties > Faculty of Information Technology |
Identification Number: | 10.1109/ICASSP.2018.8462000 |
Additional Information: | Conference code: 139797. Language of original document: English. |
URI: | http://eprints.lqdtu.edu.vn/id/eprint/9527 |