电子学报 ›› 2021, Vol. 49 ›› Issue (1): 177-182.DOI: 10.12263/DZXB.20141438

所属专题: 定位技术新进展

• 学术论文 • 上一篇    下一篇

基于协方差差分的近场源定位参量估计

秦宇镝, 孙晓颖, 刘国红   

  1. 吉林大学通信工程学院, 吉林长春 130022
  • 收稿日期:2016-05-27 修回日期:2016-11-20 出版日期:2021-01-25
    • 通讯作者:
    • 孙晓颖
    • 作者简介:
    • 秦宇镝 男,1987年7月生于吉林省长春市,吉林大学通信工程学院博士研究生.主要研究方法为阵列信号处理.E-mail:qinyd13@163.com;刘国红 女,1986年10月生于内蒙古自治区通辽市,博士研究生,主要研究方向为阵列信号处理.E-mail:liugh10@mails.jlu.edu.cn
    • 基金资助:
    • 国家自然科学基金 (No.61171137); 国家863高技术研究发展计划 (No.2013AA013704); 装备预先研究教育部支撑技术项目 (No.625010217)

Passive Localization for Near-Field Sources Based on Covariance Difference

QIN Yu-di, SUN Xiao-ying, LIU Guo-hong   

  1. Department of Communication Engineering, Jilin University, Changchun, Jilin 130022, China
  • Received:2016-05-27 Revised:2016-11-20 Online:2021-01-25 Published:2021-01-25
    • Corresponding author:
    • SUN Xiao-ying
    • Supported by:
    • National Natural Science Foundation of China (No.61171137); National High-tech R&D Program of China  (863 Program) (No.2013AA013704); Support Technology Program of Munistry of Education of China,  Weapons and equipment pre-research project (No.625010217)

摘要: 提出一种基于空间差分技术的近场源方位角和距离联合估计新算法.算法利用平稳噪声协方差矩阵关于主对角线对称的特点,构造近场源定位模型下的空间差分矩阵.推导并证明了该矩阵的谱分解特性,以此为基础确定噪声子空间,借助谱峰搜索实现定位参量估计.算法通过对消噪声分量有效降低了未知平稳噪声对定位精度的影响,同时避免了应用差分技术解决信源定位时出现的伪峰问题.均方根误差的仿真结果证明了算法的有效性.

 

关键词: 信源定位, 空间差分技术, 平稳噪声, 多重信号分类算法

Abstract: An algorithm for estimation of direction of arrival (DOA) and range of near field source based on the spatial differential technique is proposed in this paper. The algorithm firstly utilizes the feature that the stationary noise covariance matrix is symmetrical about the main diagonal and constructs the spatial difference matrix only containing the target signal location information. Then, it proves the distribution characteristics of the matrix eigenvalues and selects the noise subspace reasonably. Finally, the DOA and range estimations for near-field sources can be obtained through the spectral searching. The algorithm can effectively suppresses the unknown stationary noise and avoid the pseudo peak problems for the application of the spatial differential method when used to solve the source localization. Computer simulations confirm the satisfactory performance of the proposed algorithm.

 

Key words: source localization, spatial differential technique, stationary noise, multiple signal classification(MUSIC)

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