电子学报 ›› 2019, Vol. 47 ›› Issue (4): 848-854.DOI: 10.3969/j.issn.0372-2112.2019.04.012

• 学术论文 • 上一篇    下一篇

基于子空间技术中奇异向量分析的穿墙雷达杂波抑制方法

郑晨, 席晓莉, 宋忠国, 王梦蕾   

  1. 西安理工大学自动化与信息工程学院, 陕西西安 710048
  • 收稿日期:2017-12-22 修回日期:2018-08-21 出版日期:2019-04-25 发布日期:2019-04-25
  • 作者简介:郑晨 男,1988年生于陕西西安.现为西安理工大学自动化与信息工程学院在读博士,研究方向为穿墙雷达成像、全球导航定位接收机.E-mail:zhengchen001@126.com;席晓莉 女,1967年生于陕西西安.现为西安理工大学教授、博士生导师.研究方向为电磁理论与数值计算、无线接收与抗干扰技术等.E-mail:xixiaoli@xaut.edu.cn
  • 基金资助:
    装备预研领域基金(No.6140450010302)

A Singular Vector Stationarity Method for Clutter Mitigation in Through-the-Wall Radar Based on Subspace Method

ZHENG Chen, XI Xiao-li, SONG Zhong-guo, WANG Meng-lei   

  1. Institute of Advanced Navigation and Electromagnetics, Xi'an University of Technology, Xi'an, Shaanxi 710048, China
  • Received:2017-12-22 Revised:2018-08-21 Online:2019-04-25 Published:2019-04-25

摘要: 穿墙雷达成像中,墙体反射杂波干扰严重,严重影响目标成像效果.子空间技术对回波信号矩阵进行奇异值分解后去除墙体子空间,可以有效的抑制墙体杂波干扰,在穿墙雷达成像中具有广泛的应用.该文针对子空间技术中墙体与目标子空间的划分这一难题,提出一种基于奇异向量平稳度分类的墙体子空间提取技术.该方法利用墙体回波信号的相关特征,根据奇异值分解后各个左奇异向量的平稳程度来精确划分墙体与目标子空间.实验结果表明,与现有技术相比,该方法对墙体子空间的确定更加精准有效,提高了穿墙雷达墙体杂波干扰抑制能力,改善了墙后目标的成像质量.

关键词: 穿墙雷达, 目标探测, 奇异值分解, 子空间技术, 杂波抑制

Abstract: In Through-the-Wall Imaging (TWI),the target image is often buried in the wall reflections and other clutter waves,and the target image cannot be obtained.Subspace technique uses the received echo matrix Singular Value Decomposition (SVD) to remove the wall subspace,it is a mature technique and has broad applications in TWI.In order to distinguish the wall subspace and the target subspace,this paper presents a new wall subspace extractive method based on the stationarity of left-singular vector.SVD is applied to the echo matrix and the left-singular vectors are used to determine the subspace belonging to the wall or the target.Compared with the traditional subspace technique,this method has a better performance in wall subspace extraction.Meanwhile,the capability of suppressing wall clutter is enhanced,and the quality of the target imaging is improved.

Key words: through-the-wall imaging (TWI), target detection, singular value decomposition (SVD), subspace technique, clutter mitigation

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