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引用本文：

屈乐乐,葛亚楠,蓝晓宇.基于低秩稀疏约束的穿墙雷达成像算法[J].电讯技术，2017，57（10）： - . [点击复制]
QU Lele,GE Yanan,LAN Xiaoyu.A through-the-wall radar imaging algorithm based on low rank and sparsity constraint[J].，2017，57（10）： - . [点击复制]

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基于低秩稀疏约束的穿墙雷达成像算法
屈乐乐,葛亚楠,蓝晓宇
0 字体:加大+\|默认\|缩小-
(沈阳航空航天大学电子信息工程学院，沈阳 110136)

摘要:

针对穿墙雷达(TWR)成像过程中墙杂波与成像空间分别具有低秩性和稀疏性的特点，提出了一种基于低秩稀疏约束的穿墙雷达成像算法。所提成像算法通过奇异值软阈值法和l1范数最小化技术进行迭代求解低秩稀疏约束优化问题，实现在墙体强反射波存在的探测环境中基于压缩感知框架对墙后隐蔽目标的准确成像重建。仿真和实验数据的处理结果验证了所提成像算法的有效性和准确性。

关键词: 穿墙雷达成像算法低秩稀疏约束压缩感知

DOI：10.3969/j.issn.1001-893x.2017.10.004

基金项目:国家自然科学基金资助项目（61671310，61302172）；航空科学基金资助项目(2016ZC54013)

A through-the-wall radar imaging algorithm based on low rank and sparsity constraint

QU Lele,GE Yanan,LAN Xiaoyu

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Abstract:

By exploiting the low-rank property of the wall reflection signal and sparsity property of the observed scene,a low rank and sparsity constraint based imaging algorithm for through-the-wall radar (TWR) system is proposed. The proposed imaging method exploits the singular value soft-thresholding and l1 norm minimization technique to perform iteration to solve the low rank and sparsity constraint optimization problem. It adopts compressive sensing framework to achieve the accurate imaging reconstruction of targets behind the wall in the presence of strong wall reflection signal. The imaging results of simulation data and experimental data have verified the effectiveness and validity of the proposed imaging algorithm.

Key words: through-the-wall radar (TWR) imaging algorithm low rank sparsity constraint compressive sensing