In through-the-wall radar imaging, wall clutter mitigation and image formation are often solved separately, resulting in a suboptimal solution. This paper presents a scene reconstruction model with low rank, sparsity, and total-variation constraints that simultaneously remove the wall clutter and form the image of the scene. The proposed method exploits the low rank property of the wall clutter to remove the wall return and imposes sparsity and total variation constraints to suppress the background clutter and noise in the image. An alternating direction technique is developed to optimize the proposed model. Experimental results show that the proposed method produces images with better target to clutter ratios than delay and sum beamforming in conjunction with wall clutter mitigation and the existing low-rank and joint sparse method.

中文翻译：

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使用低秩和全变的穿墙场景重建

在穿墙雷达成像中，墙杂波抑制和图像形成通常是分开解决的，从而导致一个次优的解决方案。本文提出了一种具有低秩、稀疏性和总变化约束的场景重建模型，可同时去除墙壁杂波并形成场景图像。所提出的方法利用墙杂波的低秩特性来去除墙回波，并施加稀疏和总变化约束来抑制图像中的背景杂波和噪声。开发了一种交替方向技术来优化所提出的模型。实验结果表明，与墙杂波抑制和现有的低秩联合稀疏方法相结合，所提出的方法产生的图像具有比延迟和总和波束形成更好的目标杂波比。