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。
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 l1 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.
出处
《电讯技术》
北大核心
2017年第10期1122-1127,共6页
Telecommunication Engineering
基金
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)
关键词
穿墙雷达
成像算法
低秩
稀疏约束
压缩感知
through-the-wall radar （TWR）
imaging algorithm
low rank
sparsity constraint
compressive sensing
