基于实值特征子空间迭代的DOA估计算法

doi:10.3969/j.issn.1001-2400.2010.02.011

J4 ›› 2010, Vol. 37 ›› Issue (2): 242-247.doi: 10.3969/j.issn.1001-2400.2010.02.011

基于实值特征子空间迭代的DOA估计算法

杨雪亚;陈伯孝;朱根生

(西安电子科技大学雷达信号处理重点实验室，陕西西安 710071)

收稿日期:2009-01-05 出版日期:2010-04-20 发布日期:2010-06-03
通讯作者: 杨雪亚
作者简介:杨雪亚(1984-)，男，西安电子科技大学博士研究生，E-mail: xueya_Y@126.com．
基金资助:
国家部委预研资助项目(51307050201);2006年教育部新世纪优秀人才支持计划资助项目(NCET-06-0856);国家自然科学基金资助项目(60772068)

Novel method for DOA estimation of coherent signals by eigen-subspace iteration

YANG Xue-ya;CHEN Bai-xiao;ZHU Gen-sheng

(Key Lab. of Radar Signal Processing, Xidian Univ., Xi'an 710071， China)

Received:2009-01-05 Online:2010-04-20 Published:2010-06-03
Contact: YANG Xue-ya

摘要/Abstract

摘要：

针对相关信号的DOA估计和角度跟踪的传统算法自适应性差和特征值分解运算量大的问题，提出了一种基于实值特征子空间迭代的DOA估计算法．对每次快拍数据，通过梯度算法自适应更新信号和噪声子空间，并将复值特征子空间变换为实值，最后利用基于信号子空间的角度估计方法(Unitary ESPRIT) 或噪声子空间的方法(实值域求根MUSIC) 估计信号角度．由于引入了自适应特征子空间迭代和实值域处理，该算法无需特征值分解，有效地降低了基于子空间类高分辨算法的运算量，可以应用于相关信号的角度估计和跟踪问题．理论分析和仿真结果表明，算法具有较低的运算量和良好的自适应性，对某米波测高雷达实测数据的处理结果也表明了算法的有效性．

关键词: 波达方向估计, 实值域, 特征子空间迭代, 求根MUSIC, 旋转不变子空间技术

Abstract:

A novel method for direction-of-arrival estimation of the correlated-signal is proposed to enhance the adaptability of the traditional high-resolution methods and to reduce the computational burden caused by eigen-decomposition and searching procedure. The noise subspace or signal subspace is iteratively obtained by the gradient algorithm for each snapshot, and then it is transformed from complex-valued space to real-valued space. Finally, Unitary ESPRIT or Root-MUSIC based on real-valued space is used to estimate the angles. Introduction of the eigen-subspace iteration and real-valued space processing eliminates eigen-decomposition, thus reducing the computational complexity significantly. The method can also be applied to the angle estimation and angle tracking problems for coherent signals. Simulations and real data processing results verify the effectiveness of the proposed method.

Key words: DOA, real-valued space, eigen-subspace iteration, Root-MUSIC, ESPRIT

杨雪亚;陈伯孝;朱根生. 基于实值特征子空间迭代的DOA估计算法[J]. J4, 2010, 37(2): 242-247.

YANG Xue-ya;CHEN Bai-xiao;ZHU Gen-sheng. Novel method for DOA estimation of coherent signals by eigen-subspace iteration[J]. J4, 2010, 37(2): 242-247.

参考文献

［1］ Tadaion A A, Derakhtian M, Gazor S, Aref M R. A Fast Multiple-Source Detection and Localization Array Signal Processing Algorithm Using the Spatial Filtering and ML Approach ［J］. IEEE Trans on Signal Processing, 2007, 55(5): 1815-1827.
［2］ Wang Jin, Zhao Yongjun, Wang Zhigang. Low Complexity Subspace Fitting Method for Wideband Signal Location ［C］//5th IFIP International Conference on Wireless and Optical Communications Networks. Surabaya: IEEE, 2008: 1-4.
［3］ Zoltowski M D, Lee T S. Maximum Likelihood Based Sensor Array Signal Processing in the Beamspace Domain for Low Angle Radar Tracking ［J］. IEEE Trans on Signal Processing, 1991, 39(3): 656-671.
［4］ Zoltowski M D, Lee T S. Beamspace ML Bearing Estimation Incorporating Low-Angle Geometry ［J］. IEEE Trans on Aerospace and Electronic Systems, 1991, 27(3): 441-458.
［5］ Dong Mei, Zhang Shouhong, Wu Xiangdong, et al. A High Resolution Spatial Smoothing Algorithm ［C］//2007 International Symposium on Microwave, Antenna, Propagation and EMC Technologies for Wireless Communications. Hangzhou: IEEE, 2007: 1031-1034.
［6］ Thompson J S, Grant P M, Mulgrew B. Performance of Spatial Smoothing Algorithms for Correlated Sources ［J］. IEEE Trans on Signal Processing, 1996, 44(4): 1040-1046.
［7］ Haardt M, Nossek J A. Unitary ESPRIT: How to Obtain Increased Estimation Accuracy with a Reduced Computational Burden ［J］. IEEE Trans on Signal Processing, 1995, 43(5): 1232-1242.
［8］ Jian C, Wang S, Lin L. Two-Dimensional DOA Estimation of Coherent Signals Based on 2D Unitary ESPRIT Method ［C］//The 8th International Conference on Signal Processing. Beijing: IEEE, 2007: 16-20.
［9］ Owsley N L. Adaptive Data Orthogonalization ［C］//1978 International Conference on Acoustics, Speech, and Signal Processing.Tulsa: IEEE, 1978: 109-112.
［10］ Thompson P A. An Adaptive Spectral Analysis Technique for Unbiased Frequency Estimation in the Presence of White Noise ［C］//Proc13th Asilomar Conf Circuits, Syst Cmput. Pacific Grove: CSA, 1980: 529-533.
［11］ Durrani T S, Sharman K C. Eigenfilter Approaches to Adaptive Array Processing ［J］. IEE Proc H on Microwaves, Optics and Antennas, 1983, 130(1): 22-28.
［12］ Fuhrmann D R, Liu B. Rotational Search Methods for Adaptive Pisarenko Harmonic Retrieval ［J］. IEEE Trans on Acoustics, Speech, and Signal Processing, 1986, 34(6): 1550-1565.
［13］ Yang J F, Kaveh M. Adaptive Eigensubspace Algorithms for Direction or Frequency Estimation and Tracking［J］. IEEE Trans on Acoustics, Speech, and Signal Processing, 1988, 36(2): 241-251.
［14］ Babu K V S. A Fast Algorithm for Adaptive Estimation of Root-MUSIC Polynomial Coefficients ［C］//1991 International Conference on Acoustics, Speech, and Signal Processing. Toronto: IEEE, 1991: 2229-2232.
［15］ Pesavento M, Gershman A B, Haardt M. A Theoretical and Experimental Performance Study of a ROOT-MUSIC Algorithm Based on a Real-Valued Eigendecomposition ［C］//2000 International Conference on Acoustics, Speech, and Signal Processing. Istanbul: IEEE, 2000: 3049-3052.

[1]	王剑书,樊养余,杜瑞,吕国云. 一种用于矩形阵列的二维波达方向估计方法[J]. 西安电子科技大学学报, 2019, 46(4): 122-129.
[2]	张政和,李逸洋,张林让,刘楠. 二维面阵子空间重构快速估计方法[J]. 西安电子科技大学学报, 2019, 46(3): 32-38.
[3]	宫健;楼顺天;张伟涛. 一种强干扰条件下阵列天线波达方向估计方法[J]. 西安电子科技大学学报, 2018, 45(1): 168-172.
[4]	刘帅琦;王布宏;李龙军;李夏;曹帅. 二维混合MIMO相控阵雷达的DOA估计算法[J]. 西安电子科技大学学报, 2017, 44(3): 157-163.
[5]	赵永红;张林让;刘楠;解虎. 采用协方差矩阵稀疏表示的DOA估计方法[J]. 西安电子科技大学学报, 2016, 43(2): 58-63+101.
[6]	杨群;曹祥玉;高军;李思佳. 一种未知信源数的共形阵DOA算法[J]. J4, 2015, 42(3): 122-128.
[7]	解虎;冯大政;袁明冬. 一种采用协方差矩阵稀疏表示的DOA估计方法[J]. J4, 2015, 42(1): 35-41.
[8]	杨东;廖桂生;朱圣棋;王凯. 阵列信号降采样低秩矩阵的恢复方法[J]. J4, 2014, 41(5): 30-35.
[9]	张学敬;杨志伟;廖桂生. 半球共形阵列的两种虚拟变换方式性能对比[J]. J4, 2014, 41(3): 33-40.
[10]	刁鸣;安春莲. 独立信号与相干信号并存的二维DOA估计新方法[J]. J4, 2013, 40(5): 66-71+98.
[11]	蔡晶晶;李鹏;赵国庆. RD-MUSIC的二维DOA估计方法[J]. J4, 2013, 40(3): 81-86+144.
[12]	朱伟;陈伯孝;陈根华;杨明磊. 用干涉式APES算法实现干涉阵盲DOA估计[J]. J4, 2013, 40(1): 189-196.
[13]	王桂宝;陶海红;王兰美. 电磁矢量传感器取向误差自校正方法[J]. J4, 2012, 39(6): 66-69.
[14]	司伟建;蓝晓宇;刘学. 提高二维DOA估计分辨率的改进MUSIC算法[J]. J4, 2012, 39(2): 138-144.
[15]	杨巍;刘峥. MIMO雷达波达方向估计的性能分析[J]. J4, 2009, 36(5): 819-824.

基于实值特征子空间迭代的DOA估计算法

Novel method for DOA estimation of coherent signals by eigen-subspace iteration

PDF (PC)

赞

可视化

被引次数

摘要/Abstract

引用本文

使用本文

参考文献

相关文章 15

Metrics

本文评价

推荐阅读 0