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Joint Low-Rank and Sparse based Image Reconstruction for Through-the-Wall Radar Imaging

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conference contribution
posted on 2024-11-16, 04:11 authored by Fok Hing Chi TiviveFok Hing Chi Tivive, Abdesselam BouzerdoumAbdesselam Bouzerdoum
Through-the-wall radar uses electromagnetic waves to detect and discern targets behind opaque obstacles, such as doors and walls. Wall clutter mitigation and scene reconstruction are performed to produce the image of the behind-the-wall scene. These two problems, however, are often addressed separately, which may result in a suboptimal solution. In this paper, the wall clutter removal and image formation are unified as a joint low-rank and sparsity constrained optimization problem, which is solved using augmented Lagrange multiplier method. Experimental results shows that the proposed method produces clearer images than the existing method that uses a wall clutter mitigation method in conjunction with backprojection method for imaging.

Funding

Enhanced Through-Wall Imaging using Bayesian Compressive Sensing

Australian Research Council

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Citation

F. Tivive & A. Bouzerdoum, "Joint Low-Rank and Sparse based Image Reconstruction for Through-the-Wall Radar Imaging," in 7th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP), 2017, pp. 1-5.

Parent title

2017 IEEE 7th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, CAMSAP 2017

Volume

2017-December

Pagination

1-5

Language

English

RIS ID

125922

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