Publication Details

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.


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.

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