• 首页
  • 期刊简介
  • 编委会
  • 版权声明
  • 投稿指南
  • 期刊订阅
  • 相关下载
    雷达数据
    下载专区
  • 过刊浏览
  • 联系我们
引用本文:陈金立, 李巧雅,李家强, 陈宣. 基于协方差匹配SL0算法的MIMO雷达DOA估计[J]. 雷达科学与技术, 2019, 17(1): 19-24.[点击复制]
CHEN Jinli, LI Qiaoya,LI Jiaqiang, CHEN Xuan. DOA Estimation of MIMO Radar Based on Covariance Matching SL0 Algorithm[J]. Radar Science and Technology, 2019, 17(1): 19-24.[点击复制]
【打印本页】   【下载PDF全文】   【查看/发表评论】  【下载PDF阅读器】  【关闭】
←前一篇|后一篇→ 过刊浏览    高级检索
本文已被:浏览 6431次   下载 973次 本文二维码信息
码上扫一扫!
分享到: 微信 更多
字体:加大+|默认|缩小-
基于协方差匹配SL0算法的MIMO雷达DOA估计
陈金立, 李巧雅,李家强, 陈宣
1.南京信息工程大学气象灾害预报预警与评估协同创新中心, 江苏南京210044;2.南京信息工程大学电子与信息工程学院, 江苏南京210044;3.南京信息工程大学物理与光电工程学院, 江苏南京210044
摘要:
利用加权平滑l0范数(Smoothed l0, SL0)算法估计MIMO雷达目标DOA时,需要把协方差矩阵进行矢量化来获得相应的稀疏重构模型,并利用信号和噪声子空间的正交性来构造加权向量。然而当存在相干信源时,MIMO雷达协方差矩阵的秩将退化,这会使得稀疏重构模型的误差较大以及无法正确区分信号和噪声子空间,导致加权SL0算法的DOA估计性能恶化。针对上述问题提出了一种基于协方差匹配SL0算法的MIMO雷达DOA估计方法。该方法利用协方差匹配准则重构出一个满秩的协方差矩阵,恢复MIMO雷达协方差矩阵的Toeplitz特性,并利用协方差逆矩阵的高阶幂来近似噪声子空间从而计算加权向量。仿真分析表明,该方法能够在无需预知信源数目的情况下有效地完成对相干信号的DOA估计。
关键词:  MIMO雷达  DOA估计  SL0算法  协方差匹配
DOI:DOI: 10.3969/j.issn.1672-2337.2019.01.004
分类号:TN911.7;TN958
基金项目:国家自然科学基金(No.61302188, 61372066, 11304394); 江苏省自然科学基金(No.BK20131005)
DOA Estimation of MIMO Radar Based on Covariance Matching SL0 Algorithm
CHEN Jinli, LI Qiaoya,LI Jiaqiang, CHEN Xuan
1.Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Nanjing University of Information Science and Technology, Nanjing 210044, China;2. School of Electronic and Information Engineering, Nanjing University of Information Science and Technology, Nanjing 210044, China;3. School of Physics and Optoelectronic Engineering, Nanjing University of Information Science and Technology, Nanjing 210044, China
Abstract:
For the DOA estimation with the weighted smoothed l0(SL0) norm algorithm in MIMO radar, the vectorization of covariance matrix is needed to establish a corresponding sparse reconstruction model, and the signal and noise subspaces are used to compute the weight vector. However, due to the coherent sources, the rank of covariance matrix of MIMO radar is degenerated. Therefore, the error of the sparse reconstruction model is large and the signal and noise subspaces cannot be correctly distinguished, which will make the performance of the weighted SL0 algorithm deteriorate. A method based on covariance matching SL0 algorithm for DOA estimation in MIMO radar is proposed. A full rank covariance matrix with the property of Toeplitz is reconstructed by using the covariance matching criteria. The high-order powers of the inverse covariance matrix are used to approximate the noise subspaces for calculating the weighted vector. Experimental results demonstrate that the proposed approach can effectively achieve DOA estimation of coherent signals without knowing the number of sources.
Key words:  MIMO radar  DOA estimation  SL0 algorithm  covariance matching

版权所有:《雷达科学与技术》编辑部 备案:XXXXXXX
主办:中国电子科技集团公司第三十八研究所 地址:安徽省合肥市高新区香樟大道199号 邮政编码:230088
电话:0551-65391270 电子邮箱:radarst@163.com
技术支持:北京勤云科技发展有限公司