DOA estimation method for wideband signals by block sparse reconstruction

被引:1
|
作者
Zhen, Jiaqi [1 ]
Wang, Zhifang [1 ]
机构
[1] Heilongjiang Univ, Coll Elect Engn, Harbin 150080, Peoples R China
基金
中国国家自然科学基金;
关键词
direction of arrival (DOA) estimation; wideband signal; prolate spheroidal wave function (PSWF); block sparse reconstruction; OF-ARRIVAL ESTIMATION; GREEDY PURSUIT; LIKELIHOOD; RADAR; APPROXIMATION; ALGORITHM; RECOVERY; REPRESENTATION; MATRIX;
D O I
10.1109/JSEE.2016.00003
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
For the direction of arrival (DOA) estimation, traditional sparse reconstruction methods for wideband signals usually need many iteration times. For this problem, a new method for two-dimensional wideband signals based on block sparse reconstruction is proposed. First, a prolate spheroidal wave function (PSWF) is used to fit the wideband signals, then the block sparse reconstruction technology is employed for DOA estimation. The proposed method uses orthogonalization to choose the matching atoms, ensuring that the residual components correspond to the minimum absolute value. Meanwhile, the vectors obtained by iteration are back-disposed according to the corresponding atomic matching rules, so the extra atoms are abandoned in the course of iteration, and the residual components of current iteration are reduced. Thus the original sparse signals are reconstructed. The proposed method reduces iteration times comparing with the traditional reconstruction methods, and the estimation precision is better than the classical two-sided correlation transformation (TCT) algorithm when the snapshot is small or the signal-to-noise ratio (SNR) is low.
引用
收藏
页码:20 / 27
页数:8
相关论文
共 50 条
  • [31] Tensor Reconstruction-Based Sparse Array Interpolation for 2-D DOA Estimation of Coherent Signals
    Pavel, Md Saidur R.
    Zhang, Yimin D.
    Himed, Braham
    2024 IEEE RADAR CONFERENCE, RADARCONF 2024, 2024,
  • [32] Improved block sparse Bayesian learning based DOA estimation for massive MIMO systems?
    Liu, Zhongyan
    Liu, Yang
    Long, Xudong
    Zhang, Yinghui
    Qiu, Tianshuang
    AEU-INTERNATIONAL JOURNAL OF ELECTRONICS AND COMMUNICATIONS, 2023, 166
  • [33] Efficient Method of DOA Estimation for Coherent Signal Based on Sparse Signal Reconstruction
    Ren, Xiaoli
    Wang, Ji
    Liu, Shuangyin
    Wang, Lichen
    EIGHTH INTERNATIONAL CONFERENCE ON DIGITAL IMAGE PROCESSING (ICDIP 2016), 2016, 10033
  • [34] Wideband DOA Estimation in Spherical Harmonic Domain Using Sparse Bayesian Learning
    Zhang, Lin
    Huang, Qinghua
    Liu, Kai
    Fang, Yong
    PROCEEDINGS OF THE 36TH CHINESE CONTROL CONFERENCE (CCC 2017), 2017, : 5183 - 5187
  • [35] A New Eigen-Structure Based DOA Estimation Method for Wideband Coherent Signals
    Fathtabar, Abbas
    Khazaei, Ali Akbar
    Ghezelbigloo, Asadallah
    WIRELESS PERSONAL COMMUNICATIONS, 2021, 117 (02) : 577 - 589
  • [36] DOA estimation in monostatic MIMO array based on sparse signal reconstruction
    Shi, Wentao
    Huang, Jianguo
    Zhang, Qunfei
    Zheng, Jimeng
    2016 IEEE INTERNATIONAL CONFERENCE ON SIGNAL PROCESSING, COMMUNICATIONS AND COMPUTING (ICSPCC), 2016,
  • [37] Underdetermined DOA Estimation for Wideband Signals via Focused Atomic Norm Minimization
    Shi, Juan
    Zhang, Qunfei
    Tan, Weijie
    Mao, Linlin
    Huang, Lihuan
    Shi, Wentao
    ENTROPY, 2020, 22 (03)
  • [38] Adaptive DOA estimation with low complexity for wideband signals of massive MIMO systems
    Qiang, Xiaowei
    Liu, Yang
    Feng, Qingxia
    Zhang, Yinghui
    Qiu, Tianshuang
    Jin, Minglu
    SIGNAL PROCESSING, 2020, 176
  • [39] Joint Estimation of the DOA and the Number of Sources for Wideband Signals Using Cyclic Correntropy
    Jin, Fangxiao
    Qiu, Tianshuang
    Luan, Shengyang
    Cui, Wei
    IEEE ACCESS, 2019, 7 : 42482 - 42494
  • [40] Wideband DOA estimation based on incoherent signal subspace method
    Ahmad, Zeeshan
    Song, Yaoliang
    Du, Qiang
    COMPEL-THE INTERNATIONAL JOURNAL FOR COMPUTATION AND MATHEMATICS IN ELECTRICAL AND ELECTRONIC ENGINEERING, 2018, 37 (03) : 1271 - 1289