Real-Valued DOA Estimation Utilizing Enhanced Covariance Matrix With Unknown Mutual Coupling

被引:10
|
作者
Tian, Ye [1 ]
Wang, Ran [2 ]
Chen, Hua [1 ]
Qin, Yunbai [3 ]
Jin, Ming [1 ]
机构
[1] Ningbo Univ, Fac Informat Sci & Engn, Ningbo 315211, Peoples R China
[2] Yanshan Univ, Sch Informat Sci & Engn, Qinhuangdao 066004, Hebei, Peoples R China
[3] Guangxi Normal Univ, Sch Elect Engn, Guilin 541004, Peoples R China
基金
中国国家自然科学基金;
关键词
Estimation; Covariance matrices; Direction-of-arrival estimation; Mutual coupling; Massive MIMO; Eigenvalues and eigenfunctions; Convolutional neural networks; Direction of arrival (DOA) estimation; enhanced covariance estimation; unknown mutual coupling; RBLW estimator; real-valued transformation; SPARSE REPRESENTATION; ARRAY;
D O I
10.1109/LCOMM.2022.3148260
中图分类号
TN [电子技术、通信技术];
学科分类号
0809 ;
摘要
Due to the space limitations, the array in a massive multiple-input multiple-output (MIMO) system often suffers from unknown mutual coupling. Meanwhile, small records of data observations may coexist. Such two limitations bring a challenge for accurate direction-of-arrival (DOA) estimation. To conquer this challenge, a real-valued DOA estimation method is proposed in this letter, whose core is to eliminate the influence of unknown mutual coupling by the inherent mechanism, as well as enhance the sampled covariance matrix estimation with the linear shrinkage technique combined with Rao-Blackwell Ledoit-Wolf (RBLW) estimator under the case of small sample size. Considering the result that the direct usage of the shrinkage target of RBLW estimator can yield an improved DOA estimation under low SNRs, a modified method depends on the eigenvalue comparison is also addressed. Simulation results show that the proposed method can provided an increased accuracy with reduced complexity.
引用
收藏
页码:912 / 916
页数:5
相关论文
共 50 条
  • [41] Real-valued off-grid DOA estimation via iterative optimisation based on covariance differencing method with spatial coloured noise
    Pan, Meihong
    Zhang, Gong
    Hu, Zhentao
    Zheng, Qin
    IET RADAR SONAR AND NAVIGATION, 2019, 13 (07): : 1116 - 1122
  • [42] Estimation of mutual information for real-valued data with error bars and controlled bias
    Holmes, Caroline M.
    Nemenman, Ilya
    PHYSICAL REVIEW E, 2019, 100 (02)
  • [43] Real-valued DOA estimation for a mixture of uncorrelated and coherent sources via unitary transformation
    Si, Weijian
    Zhao, Pinjiao
    Qu, Zhiyu
    Wang, Yan
    DIGITAL SIGNAL PROCESSING, 2016, 58 : 102 - 114
  • [44] Effective Block Sparse Representation Algorithm for DOA Estimation With Unknown Mutual Coupling
    Wang, Qing
    Dou, Tongdong
    Chen, Hua
    Yan, Weiqing
    Liu, Wei
    IEEE COMMUNICATIONS LETTERS, 2017, 21 (12) : 2622 - 2625
  • [45] A Novel Block Sparse Reconstruction Method for DOA Estimation With Unknown Mutual Coupling
    Zhang, Xiaowei
    Jiang, Tao
    Li, Yingsong
    Zakharov, Yuriy
    IEEE COMMUNICATIONS LETTERS, 2019, 23 (10) : 1845 - 1848
  • [46] Real-Valued Weighted Subspace Fitting Algorithm for DOA Estimation with Block Sparse Recovery
    Li, Liangliang
    Wang, Xianpeng
    Shi, Jinmei
    Lan, Xiang
    MATHEMATICAL PROBLEMS IN ENGINEERING, 2023, 2023
  • [47] DOA estimation based on fourth-order cumulants with unknown mutual coupling
    Liu, Chao
    Ye, Zhongfu
    Zhang, Yufeng
    SIGNAL PROCESSING, 2009, 89 (09) : 1839 - 1843
  • [48] A DOA Estimation Method in the presence of unknown mutual coupling based on Nested Arrays
    Xie, Julan
    Cheng, Fanghao
    He, Zishu
    Li, Huiyong
    2019 ASIA-PACIFIC SIGNAL AND INFORMATION PROCESSING ASSOCIATION ANNUAL SUMMIT AND CONFERENCE (APSIPA ASC), 2019, : 1066 - 1071
  • [49] Robust DOA Estimation for MIMO Radar in Unknown Nonuniform Noise and Mutual Coupling
    Wang, Xianpeng
    Huang, Mengxing
    Shen, Chong
    Cao, Chunjie
    Zhang, Kun
    Bi, Guoan
    2018 IEEE 10TH SENSOR ARRAY AND MULTICHANNEL SIGNAL PROCESSING WORKSHOP (SAM), 2018, : 194 - 197
  • [50] Compressed Sensing-Based DOA Estimation with Unknown Mutual Coupling Effect
    Chen, Peng
    Cao, Zhenxin
    Chen, Zhimin
    Liu, Linxi
    Feng, Man
    ELECTRONICS, 2018, 7 (12):