系统工程与电子技术 ›› 2021, Vol. 43 ›› Issue (6): 1477-1485.doi: 10.12305/j.issn.1001-506X.2021.06.04

• 雷达抗干扰技术 • 上一篇    下一篇

空域色噪声背景下双基地MIMO雷达角度估计

师俊朋1, 文方青2,3,*, 艾林3, 张弓4, 龚政辉1   

  1. 1. 国防科技大学电子科学与工程学院, 湖南 长沙 410073
    2. 三峡大学计算机与信息学院, 湖北 宜昌 443002
    3. 长江大学电子信息学院, 湖北 荆州 434200
    4. 南京航空航天大学电子信息工程学院, 江苏 南京 210016
  • 收稿日期:2020-11-16 出版日期:2021-05-21 发布日期:2021-05-28
  • 通讯作者: 文方青
  • 作者简介:师俊朋(1988—), 男, 副教授, 博士, 主要研究方向为压缩感知、张量分解、雷达信号处理|文方青(1988—), 男, 副教授, 博士, 主要研究方向为压缩感知、雷达信号处理|艾林(1990—), 男, 博士研究生, 主要研究方向为阵列信号处理、张量分析|张弓(1964—), 男, 教授, 博士研究生导师, 博士, 主要研究方向为目标探测与识别、雷达信号处理、压缩感知、图像分析与处理|龚政辉(1988—), 男, 博士研究生, 主要研究方向为压缩感知、雷达信号处理
  • 基金资助:
    国家自然科学基金(62071476);国家自然科学基金(61871218);国家自然科学基金(61701046);国家自然科学基金(61921001);中央高校基本科研业务费专项资金;江苏高校优势学科建设工程;湖南省科技创新计划(2020RC2041);中国博士后面上资助项目;国防科技大学学校科研计划(ZK20-33)

Angle estimation for bistatic MIMO radar with spatially colored noise

Junpeng SHI1, Fangqing WEN2,3,*, Lin AI3, Gong ZHANG4, Zhenghui GONG1   

  1. 1. School of Electronic Science and Engineering, National University of Defense Technology, Changsha 410073, China
    2. College of Computer and Information Technology, China Three Gorges University, Yichang 443002, China
    3. School of Electronics and Information, Yangtze University, Jingzhou 434200, China
    4. College of Electronics and Information Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China
  • Received:2020-11-16 Online:2021-05-21 Published:2021-05-28
  • Contact: Fangqing WEN

摘要:

空域有色噪声会导致现有多输入多输出(multiple input multiple output, MIMO)雷达算法性能下降, 甚至完全失效。针对空域色噪声背景下双基地MIMO雷达联合波离角(direction of departure, DOD)和波达角(direction of arrival, DOA)估计问题, 分析了现有算法失效的原因。考虑到匹配滤波后无噪协方差矩阵的低秩特性、色噪声协方差矩阵的稀疏特性以及MIMO雷达数据的多维结构特性, 提出一种基于张量分析的角度估计算法。首先, 构造角度估计的协方差张量, 通过去除协方差张量中受噪声协方差影响的元素对色噪声进行抑制。其次,利用张量填充技术对无噪协方差矩阵进行恢复。然后,利用平行因子分解获得目标角度的方向矩阵。最后, 采用最小二乘算法对目标的DOA和DOD进行拟合。仿真结果表明, 所提算法对色噪声不敏感, 且无孔径损失。相比现有矩阵及张量分析算法, 所提算法具有更高的估计精度。

关键词: 多输入多输出雷达, 波离角和波达角估计, 空域色噪声, 张量填充, 平行因子分解

Abstract:

Spatially colored noise would lead to performance degradation or even invalidation of multiple input multiple output (MIMO) radar algorithms. For the problem of joint direction of departure (DOD) and direction of arrival (DOA) estimation in bistatic MIMO radar with spatially colored noise, the reason for the failure of the existing algorithms is analyzed. Taking the low-rank property of the noiseless covariance matrix, the sparse feature of the colored noise covariance matrix as well as the multidimensional structure characteristic of the MIMO radar data after matched filtering into consideration, a tensor analysis-based angle estimation is introduced. Firstly, a covariance tensor for the angle estimation is constructed. The colored noise is suppressed via removing the entities that affected by the noise covariance measurement. Then the noiseless covariance tensor is recovered via tensor completion. Thereafter, the factor matrices corresponding to DOD and DOA are achieved via parallel factor (PARAFAC) decomposition. Finally, the DOD and DOA are fitted using least squares algorithm. Simulation results show that the proposed algorithm is not sensitive to the spatially colored noise, and it is free-from the aperture loss. The proposed algorithm performs more accurate estimation performance than the existing matrix and tensor approaches.

Key words: multiple input multiple output (MIMO) radar, direction of departure (DOD) and direction of arrival (DOA) estimation, spatially colored noise, tensor completion, parallel factor (PARAFAC) decomposition

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