吉林大学学报(工学版) ›› 2017, Vol. 47 ›› Issue (1): 268-273.doi: 10.13229/j.cnki.jdxbgxb201701039

• 论文 • 上一篇    下一篇

基于特征空间MUSIC算法的相干信号波达方向空间平滑估计

石要武1, 陈淼1, 单泽涛2, 石屹然1, 单泽彪1, 3   

  1. 1.吉林大学 通信工程学院,长春 130022;
    2.诺博橡胶制品有限公司, 河北 保定 072550;
    3.长春理工大学 电子信息工程学院,长春 130022
  • 收稿日期:2015-09-09 出版日期:2017-01-20 发布日期:2017-01-20
  • 作者简介:石要武(1954-),男,教授,博士生导师.研究方向:现代信号处理.E-mail:shiyw@jlu.edu.cn
  • 基金资助:
    国家自然科学基金项目(61571462); 吉林省青年科研基金项目(20140520064JH).

Spatial smoothing technique for coherent signal DOA estimation based on eigen space MUSIC algorithm

SHI Yao-wu1, CHEN Miao1, SHAN Ze-tao2, SHI Yi-ran1, SHAN Ze-biao1, 3   

  1. 1.College of Communication Engineering, Jilin University, Changchun 130022, China;
    2.Nuobo Rubber Production Co., Ltd., Baoding 072550,China;
    3.School of Electronic and Information Engineering, Changchun University of Science and Technology, Changchun 130022, China
  • Received:2015-09-09 Online:2017-01-20 Published:2017-01-20

摘要: 为了高效、准确地估计相干信号的波达方向(DOA),提出了一种基于特征空间多重信号分类(MUSIC)算法的空间平滑估计方法。首先对相干信号进行空间平滑处理,然后对其应用特征空间MUSIC算法进行DOA的精确估计,使其最大限度地利用信号子空间和噪声子空间的信息。本文方法并不影响非相关信号存在时DOA的估计,且还可以对信号源功率进行有效的估计,以提高对小能量信号的成功估计概率。与传统空间平滑算法及修正MUSIC算法相比,本文方法具有更低的信噪比门限和更高的估计精度及分辨力。最后的仿真实验验证了本文方法的有效性和鲁棒性。

关键词: 信息处理技术, 波达方向估计, 相干信号, 特征空间, 空间平滑技术, 信号源功率估计

Abstract: To estimate the Direction of Arrival (DOA) of coherent signals accurately and quickly, a new decorrelation method based on spatial smoothing technique and eigen space multiple signal classification (MUSIC) is presented. After spatial smoothing of the coherent signals, the eigen space MUSIC algorithm is applied to estimate the DOA in order to make maximal use of the information of signal and noise subspaces. In addition, the DOA estimation of uncorrelated signals is not affected, as well as the power of signal sources can be estimated effectively, which can improve the probability of success in the estimation of low power signals. The proposed method possesses a better resolving ability and a lower SHR threshold than conventional spatial smoothing technique and modified MUSIC algorithm for DOA estimation of coherent signals. The simulation results demonstrate that the proposed method is effective and robust in DOA estimation.

Key words: information processing, direction of arrival(DOA) estimation, coherent signal, eigen space, spatial smoothing technique, signal source power estimation

中图分类号: 

  • TN911
[1] 王布宏, 王永良, 陈辉. 相干信源波达方向估计的加权空间平滑算法[J]. 通信学报, 2003, 24(4):31-40.
Wang Bu-hong, Wang Yong-liang, Chen Hui. Weighted spatial smoothing algorithm for direction of arrival estimation of coherent sources[J]. Journal on Communications, 2003, 24(4): 31-40.
[2] Qian C, Huang L, Zeng W J, et al. Direction-of-arrival estimation for coherent signals without knowledge of source number[J]. IEEE Sensors Journal, 2014,14(9): 3267-3273.
[3] Tao H, Xin J M, Wand J S, et al.Two-dimensional direction estimation for a mixture of noncoherent and coherent signals[J]. IEEE Transactions on Signal Processing, 2014,63(2):318-333.
[4] Stoica P, Arye N. Music, maximum likelihood, and cramer-rao bound[J]. IEEE Transactions on Acoustics Speech and Signal Procession, 1989, 373(5):720-741.
[5] Linebarger D A. Redundancy averaging with large arrays[J]. IEEE Transactions on Signal Processing, 1993, 41(4):1707-1710.
[6] Evans J E, Johnson J R,Sun D F. High resolution angular spectrum estimation techniques for terrain scattering analysis and angle of arrival estimation[C]∥Processing 1st ASSP Workshop Spectral Estimation, Hamilton, Ontario Canada, 1981: 134-139.
[7] Shan T J, Wax M,Lailath T. On spatial smoothing for estimation of coherent signals[J]. IEEE Transactions on Acoustics Speech and Signal Processing, 1985, 33(4): 806-811.
[8] Pillai S U, Kwon B H. Forward/backward spatial smoothing techniques for coherent signal identification[J]. IEEE Transactions on Acoustics Speech and Signal Processing, 1989, 37(1):8-15.
[9] Todros K, Hero A O. Robust multiple signal classification via probability measure transformation[J]. IEEE Transactions on Signal Processing, 2015,63(5): 1156-1170.
[10] Zhang W, Liu W, Wang J, et al. Joint transmission and reception diversity smoothing for direction finding of coherent targets in MIMO radar[J]. IEEE Journal of Selected Topics in Signal Processing, 2014, 8(1):115-124.
[11] Kundu D. Modified MUSIC algorithm for estimating DOA of signals[J]. Signal Processing, 1996, 48(1): 85-90.
[12] Zhang X F, Lü W, Shi Y,et al. A novel DOA estimation algorithm based on eigen space[C]∥IEEE International Symposium on Microwave, Antenna, Propagation and EMC Technologies for Wireless Communications, Hangzhou, China,2007: 551-554.
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