基于鲁棒主成分分析的混沌穿墙成像雷达杂波抑制方法  

Clutter Removal Using Robust Principal Component Analysis for Chaos Through-Wall Imaging Radar

作　　者：韩银萍 刘丽[1,2] 王冰洁 徐航[1,2] 李静霞 HAN Yinping;LIU Li;WANG Bingjie;XU Hang;LI Jingxia(Key Laboratory of Advanced Transducers and Intelligent Control System of Ministry of Education and Shanxi Province,Taiyuan University of Technology,Taiyuan 030024,China;College of Physics and Optoelectronics,Taiyuan University of Technology,Taiyuan 030024,China)

机构地区：[1]太原理工大学新型传感器与智能控制教育部和山西省重点实验室,太原030024 [2]太原理工大学物理与光电工程学院,太原030024

出　　处：《电子器件》2020年第1期142-146,共5页Chinese Journal of Electron Devices

基　　金：国家自然科学基金项目(41704147,41604127,61601319);山西省自然科学基金项目(201803D31037,201703D321036)。

摘　　要：针对混沌穿墙成像雷达的杂波抑制问题,提出一种基于鲁棒主成分分析的杂波抑制方法。该方法首先通过互相关计算得到原始数据,并利用后向投影法聚焦目标能量,提高数据的稀疏性,然后利用鲁棒主成分分析法对聚焦后的数据进行低秩稀疏矩阵分解,从而抑制杂波。实验结果表明,该方法得到的图像信杂比高达20.69 dB,能有效去除杂波干扰,并实现人体目标的精确定位。与传统方法相比,该方法能大幅度提高图像的信杂比,改善成像质量。A clutter suppression method based on robust principal component analysis(RPCA)is proposed for chaotic through-wall imaging radar.Firstly,the original data is obtained by cross-correlation calculation,and the target energy is focused by the back projection method to improve the sparsity of the original data.Then robust principal component analysis is used to sparse and low-rank matrix decomposition to suppress the clutter.Experimental results show that the signal-clutter ratio of the image obtained by this method is 20.69 dB,it can effectively remove the clutter and realize the precise location of the human target.Compared with the traditional methods,this method can greatly improve the signal-to-clutter ratio of the image and enhance the imaging quality.

关 键 词：雷达 杂波抑制 混沌相关 鲁棒主成分分析 后向投影 

分 类 号：TN95[电子电信—信号与信息处理]