A New DOA Estimation Algorithm Based on PSO-Gauss-Newton

被引:4
作者
Cui, Xuerong [1 ]
Zhou, Rongrong [1 ]
Chen, Haihua [2 ]
Zhang, Yucheng [3 ]
Li, Shibao [1 ]
Zhang, Jingyao [1 ]
机构
[1] China Univ Petr, Coll Oceanog & Space Informat, Qingdao, Peoples R China
[2] Chinese Acad Sci, Inst Comp Technol, Beijing, Peoples R China
[3] Chinese Acad Sci, Engn Lab Intelligent Agr Machinery Equipment, Beijing, Peoples R China
来源
2021 IEEE 9TH INTERNATIONAL CONFERENCE ON INFORMATION, COMMUNICATION AND NETWORKS (ICICN 2021) | 2021年
基金
中国国家自然科学基金;
关键词
direction-of-arrival; stochastic maximum likelihood algorithm; computational complexity; limited solution space; Gauss-newton algorithm;
D O I
10.1109/ICICN52636.2021.9673931
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Direction-of-Arrival (DOA) estimation is a basic and important problem in sensor array signal processing. In order to solve this problem, many algorithms have been proposed. Among them, the Stochastic Maximum Likelihood (SML) algorithm has become one of the most concerned algorithms because of its high DOA accuracy. However, the computational complexity of SML algorithm is very high, so Gauss-Newton algorithm is used as the analytical algorithm of SML in this paper. The traditional Gauss-Newton algorithm used in DOA estimation has some defects: (1) over reliance on the choice of initial values (2) fall into local optimum easily. In order to solve these defects and further reduce the computational complexity, this paper proposes a new DOA estimation algorithm based on PSO-Gauss-Newton. First of all, a limited solution space is proposed based on the precondition that the estimated signal must be non-negative definite. Then, according to the idea of PSO(Particle Swarm Optimization) algorithm, multiple scattering points are randomly distributed in the limited solution space. Each initial particle performs Gauss-Newton algorithm iteration separately. Finally, the global optimal solution is determined by comparison of all the convergence values. Simulation results the computational complexity of this algorithm is almost comparable to that of MUSIC algorithm.
引用
收藏
页码:81 / 85
页数:5
相关论文
共 12 条
[1]   Stochastic maximum-likelihood DOA estimation in the presence of unknown nonuniform noise [J].
Chen, Chiao En ;
Lorenzelli, Flavio ;
Hudson, Ralph. E. ;
Yao, Kung .
IEEE TRANSACTIONS ON SIGNAL PROCESSING, 2008, 56 (07) :3038-3044
[2]  
Chen HH, 2015, 2015 15TH INTERNATIONAL SYMPOSIUM ON COMMUNICATIONS AND INFORMATION TECHNOLOGIES (ISCIT), P189, DOI 10.1109/ISCIT.2015.7458339
[3]  
CHEN Haihua, 2010, I ELECT INFORM COMMU, V93
[4]   Extended DOA-Matrix Method for DOA Estimation via Two Parallel Linear Arrays [J].
Dai, Xiangrui ;
Zhang, Xiaofei ;
Wang, Yunfei .
IEEE COMMUNICATIONS LETTERS, 2019, 23 (11) :1981-1984
[5]  
Demirli R, 1998, ULTRASON, P831, DOI 10.1109/ULTSYM.1998.762272
[6]  
Park CS, 2009, 11TH INTERNATIONAL CONFERENCE ON ADVANCED COMMUNICATION TECHNOLOGY, VOLS I-III, PROCEEDINGS,, P2295
[7]  
Pour H. M., 2016, MOBILE COMPUTING WIR
[8]  
Pratt RG, 1998, GEOPHYS J INT, V133, P341, DOI 10.1046/j.1365-246X.1998.00498.x
[9]  
Vikas B, 2017, 2017 INTERNATIONAL CONFERENCE OF ELECTRONICS, COMMUNICATION AND AEROSPACE TECHNOLOGY (ICECA), VOL 2, P403, DOI 10.1109/ICECA.2017.8212844
[10]  
[姚磊华 Yao Leihua], 2005, [岩土工程学报, Chinese Journal of Geotechnical Engineering], V27, P885