• 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,蒋志军,朱熙铖,李家强. 基于矩阵因子重构的MIMO雷达角度估计方法[J]. 雷达科学与技术, 2023, 21(6): 653-660.[点击复制]
CHEN Jinli, JIANG Zhijun, ZHU Xicheng, LI Jiaqiang. Angle Estimation Method in MIMO Radar Based on Matrix Factor Reconstruction[J]. Radar Science and Technology, 2023, 21(6): 653-660.[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 4681次   下载 542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-
基于矩阵因子重构的MIMO雷达角度估计方法
陈金立,蒋志军,朱熙铖,李家强
南京信息工程大学电子与信息学院, 江苏南京 210044
摘要:
多输入多输出(MIMO)雷达中部分失效阵元会使得阵列采样数据丢失,从而导致较差的角度估计性能。为此,提出一种基于不完整矩阵因子重构的MIMO雷达角度估计方法。首先,根据协方差矩阵可分解的性质,提取维度较低的矩阵因子,并将协方差矩阵中缺失数据恢复问题转化为矩阵因子重构问题。然后,为了利用矩阵因子中元素的相关性,对不完整矩阵因子建立核范数约束下的低秩Hankel矩阵重构模型;为避免传统的核范数最小化求解中计算复杂度高的问题,采用低秩矩阵拟合方法将Hankel矩阵分解为两个维度较低的矩阵,等价表达了核范数约束。最后,利用交替方向乘子法(ADMM)对该矩阵重构模型进行求解。仿真结果表明,本文方法可以有效地重构出矩阵因子中的缺失元素,进而实现阵列协方差矩阵中丢失数据的补全,改善阵元失效下的MIMO雷达角度估计性能。
关键词:  MIMO雷达  阵元失效  角度估计  Hankel矩阵  矩阵因子重构
DOI:DOI:10.3969/j.issn.1672-2337.2023.06.009
分类号:TN911.23;TN958
基金项目:国家自然科学基金(No.62071238);江苏省自然科学基金(No.BK20191399)
Angle Estimation Method in MIMO Radar Based on Matrix Factor Reconstruction
CHEN Jinli, JIANG Zhijun, ZHU Xicheng, LI Jiaqiang
School of Electronics and Information Engineering, Nanjing University of Information Science and Technology, Nanjing 210044, China
Abstract:
Partial failed elements in multiple input multiple output(MIMO) radar may result in the loss of array sampling data and thus poor angle estimation performance. To mitigate this performance degradation,a novel MIMO radar angle estimation method is proposed based on incomplete matrix factor reconstruction. The method firstly utilizes the decomposability property of the covariance matrix to extract the low?dimensional matrix factor, transforming the problem of missing data recovery in the covariance matrix into a problem of reconstructing the matrix factor. Afterwards, a low?rank Hankel matrix reconstruction model is established by exploiting the correlation between the elements in the matrix factor and imposing a nuclear norm constraint on the incomplete matrix factor. To avoid the high computational complexity of the traditional nuclear norm minimization problem, this method decomposes the Hankel matrix into two lower?dimensional matrices using the low?rank matrix fitting method. This realizes an equivalent representation of the nuclear norm constraint. Finally, the alternating direction method of multipliers(ADMM) is employed to solve the matrix reconstruction model. Simulation results demonstrate the effectiveness of the proposed method in reconstructing the missing elements within matrix factors, thereby completing lost entries in array sampling data and improving angle estimation performance for MIMO radar under element failure.
Key words:  MIMO radar  array element failure  angle estimation  Hankel matrix  matrix factor reconstruction

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