吉林大学学报(信息科学版) ›› 2020, Vol. 38 ›› Issue (3): 237-242.

• •    下一篇

基于黎曼流形的MIMO雷达目标检测方法

周美含,姜宏,孙帅   

  1. 吉林大学通信工程学院,长春130012
  • 收稿日期:2019-11-12 出版日期:2020-05-24 发布日期:2020-06-23
  • 作者简介:周美含( 1994— ) ,女,吉林松原人,吉林大学硕士研究生,主要从事雷达目标检测研究,( Tel) 86-15568998358 ( E-mail)zhoumh17@ mails. jlu. edu. cn; 姜宏( 1966— ) ,女,长春人,吉林大学教授,博士生导师,主要从事阵列信号处理以及信号检测与估计研究,( Tel) 86-13086816575( E-mail) jiangh@ jlu. edu. cn。
  • 基金资助:
    国家自然科学基金资助项目( 61371158)

Target Detection Method for MIMO Radar Based on Riemannian Manifold

ZHOU Meihan,JIANG Hong,SUN Shuai   

  1. College of Communication Engineering,Jilin University,Changchun 130012,China
  • Received:2019-11-12 Online:2020-05-24 Published:2020-06-23

摘要: 针对样本数少时不能用样本协方差代替统计协方差的问题,提出了一种基于黎曼流形的单基地MIMO
( Multiple-Input Multiple-Output) 雷达目标检测新方法。该方法利用拓普利兹-厄米特正定( THPD: Toeplitz-
Hermitian Positive Definite) 矩阵会在信号空间形成黎曼流形的特点,通过burg 递推法分别生成单快拍下接收信
号和噪声的THPD 协方差矩阵,并计算噪声THPD 协方差矩阵的黎曼均值,将其与接收信号THPD 协方差矩阵
之间的黎曼距离作为检测统计量。该方法可增加黎曼流形上接收信号与噪声间的差异性。仿真结果表明,
与传统的基于欧几里得距离的检测方法相比,显著提高了低信噪比和单快拍下的目标检测性能。

关键词: 雷达工程, 目标检测, 黎曼流形, burg 递推法

Abstract: Aiming at the problem that the sample covariance can not replace the statistical covariance when the
number of samples is small,a novel target detection method based on Riemannian manifold is proposed for
monostatic MIMO( Multiple-Input Multiple-Output) radar. It takes advantage of the fact that the THPD( Toeplitz-
Hermitian Positive Definite) matrix can form Riemannian manifold in signal space. The single-snapshot THPD
covariance matrices of received signals and noises are respectively generated through the burg algorithm,and the
Riemannian mean of the noise THPD covariance matrices is calculated. The Riemannian distance between the
THPD covariance matrices of received signal and noise is taken as the detection statistic. The method can
increase the dissimilarity between the received signal and noise on the Riemannian manifold. The simulation
results indicate that compared to the traditional method which uses the Euclidean distance,the proposed method
can significantly improve the target detection performance under low SNR ( Signal-to-Noise Ratio) and singlesnapshot.

Key words: radar engineering, target detection, riemannian manifold, burg algorithm

中图分类号: 

  • TN911. 23