电子学报 ›› 2019, Vol. 47 ›› Issue (12): 2480-2487.DOI: 10.3969/j.issn.0372-2112.2019.12.005

• 学术论文 • 上一篇    下一篇

低信噪比双基地MIMO雷达目标角度跟踪算法

张正言1, 张剑云2, 郑志东3, 李小波2   

  1. 1. 75775部队, 广东广州 510010;
    2. 国防科技大学电子对抗学院, 安徽合肥 230037;
    3. 32802部队, 北京 100191
  • 收稿日期:2017-10-24 修回日期:2018-10-13 出版日期:2019-12-25 发布日期:2019-12-25
  • 通讯作者: 郑志东
  • 作者简介:张正言 男,博士,国防科技大学电子对抗学院,主要研究方向:阵列信号处理,MIMO雷达信号处理.E-mail:zzyaisj@163.com;张剑云 男,国防科技大学电子对抗学院教授,主要研究方向:雷达及目标环境模拟,雷达信号处理,高速信号处理.E-mail:zjy921@sina.com;李小波 男,国防科技大学电子对抗学院教授,主要研究方向为雷达信号处理,高速数字信号处理.E-mail:lxb_eei@163.com
  • 基金资助:
    国家自然科学基金(No.61671453,No.61201379);安徽省自然科学基金(No.1608085MF123)

Target Angle Tracking Algorithm of Bistatic MIMO Radar with Low Signal-to-Noise Ratio

ZHANG Zheng-yan1, ZHANG Jian-yun2, ZHENG Zhi-dong3, LI Xiao-bo2   

  1. 1. Troop 75775, Guangzhou, Guangdong 510010, China;
    2. National University of Defense Technology, Hefei, Anhui 230037, China;
    3. Troop 32802, Beijing 100191, China
  • Received:2017-10-24 Revised:2018-10-13 Online:2019-12-25 Published:2019-12-25

摘要: 研究了低信噪比时双基地MIMO雷达目标跟踪问题,提出了一种基于改进AAJD(Adaptive Asymmetric Joint Diagonalization)的目标跟踪算法.首先,对AAJD算法进行改进,得到与特征值作用相同的变量,从而找出大特征值变量对应的特征矢量,解决了低信噪比时AAJD算法信号子空间扩展问题.其次,在非稳定跟踪状态时消除特征值变量误差积累的影响,得到更加准确的信号子空间,并对ESPRIT算法进行改进,实现收发角度的配对和相邻时刻角度的自动关联.仿真结果表明改进AAJD算法低信噪比时能够实现角度跟踪,且收敛速度和稳定性能明显优于AAJD算法.

关键词: 双基地MIMO雷达, 角度跟踪, 特征值变量, 扩展信号子空间, 角度配对和关联

Abstract: The target tracking problem of bistatic MIMO radar under low SNR is studied,and a target tracking algorithm based on the improved AAJD(Adaptive Asymmetric Joint Diagonalization)is proposed.Firstly,the AAJD algorithm is improved to obtain the variable as the eigenvalue and the criterion of selecting the feature vector.The eigenvalue variables are used to find the eigenvectors corresponding to the large eigenvalue variables.And the problem of signal subspace expansion in AAJD algorithm is solved at low SNR.Secondly,the influence of the accumulation of the eigenvalue variables error is eliminated in the unsteady tracking state.The obtained signal subspace is more accurate.Since the estimated eigenvectors order is random at each time,the ESPRIT algorithm is improved to achieve the automatic pairing of transceiver angle of the same moment and the automatic association of the angle of the adjacent moment.The simulation results show that the improved AAJD algorithm can realize the angle tracking with low signal to noise ratio,and the convergence speed and stability performance are significantly better than AAJD algorithm.

Key words: bistatic MIMO radar, angle tracking, eigenvalue variable, extended signal subspace, angle pairing and association

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