DOA estimation of incoherently distributed sources using importance sampling maximum likelihood

doi:10.23919/JSEE.2022.000070

Journal of Systems Engineering and Electronics ›› 2022, Vol. 33 ›› Issue (4): 845-855.doi: 10.23919/JSEE.2022.000070

• ELECTRONICS TECHNOLOGY • Previous Articles Next Articles

DOA estimation of incoherently distributed sources using importance sampling maximum likelihood

Tao WU^1,²(), Zhenghong DENG^1,*(), Xiaoxiang HU(), Ao LI(), Jiwei XU³()

¹ School of Automation, Northwestern Polytechnical University, Xi’an 710072, China
² Equipment Management and UAV College, Air Force Engineering University, Xi’an 710051, China
³ School of Information Engineering, Xi’an University of Posts and Telecommunications, Xi’an 710061, China

Received:2021-09-26 Accepted:2022-04-25 Online:2022-08-30 Published:2022-08-30
Contact: Zhenghong DENG E-mail:taowu_nwpu@126.com;dthree@nwpu.edu.cn;xxhu@nwpu.edu;ao.li@mail.nwpu.edu.cn;xu@xupt.edu.cn
About author:|WU Tao was born in 1984, He obtained his B.S. degree in electronic engineering in 2005 and M.S. degree in system engineering in 2008. He is currently pursuing his Ph.D. degree in Automation School of Northwest Polytechnic University. He is a lecturer and has been engaged in teaching and scientific research of array signal processing and system modelling and simulation. He has published more than 10 papers. His main research interests are array signal processing and complex system modelling and simulation. E-mail: taowu_nwpu@126.com||DENG Zhenghong was born in 1974. He received his M.S. degree in computer science and engineering in 1999 and Ph.D. degree from Northwestern Polytechnical University in 2002, respectively. Currently, he is a professor at Automation School of Northwest Polytechnic University. In 2013, he was invited to University of Victoria in Canada as a short-term research fellow. His main research interests include statistical signal processing, array signal processing, underwater acoustical image processing, and acoustic localization. E-mail: dthree@nwpu.edu.cn||HU Xiaoxiang was born in 1982. He received his M.S. degree in guidance, navigation, and control, and Ph.D. degree in control science and engineering from the Xi’an Research Institute of High-Tech, Xi’an, China, in 2008 and 2012, respectively. He is currently an associate professor in the School of Automation, Northwestern Polytechnical University. His current research interests include fuzzy control, sliding mode control, and hypersonic flight vehicles. E-mail: xxhu@nwpu.edu||LI Ao was born in 1993. He received his B.S. degree in electronic engineering and automation in 2014, and M.S. degree in electronic engineering in 2018. He is currently pursuing his Ph.D. degree in the School of Automation, Northwest Polytechnic University. His main research interests are model predict control and cooperative control of UAVs. E-mail: ao.li@mail.nwpu.edu.cn||XU Jiwei was born in 1986. He obtained his M.S. degree in signal processing engineering in 2014 and Ph.D. degree from Northwestern Polytechnical University in 2019. He is an associate professor with Xi’an University of Posts and Telecommunications. His research interests include underwater signal processing and sensor network E-mail: xu@xupt.edu.cn
Supported by:
This work was supported by the basic research program of Natural Science in Shannxi province of China (2021JQ-369).

Abstract

Abstract:

In this paper, an importance sampling maximum likelihood (ISML) estimator for direction-of-arrival (DOA) of incoherently distributed (ID) sources is proposed. Starting from the maximum likelihood estimation description of the uniform linear array (ULA), a decoupled concentrated likelihood function (CLF) is presented. A new objective function based on CLF which can obtain a closed-form solution of global maximum is constructed according to Pincus theorem. To obtain the optimal value of the objective function which is a complex high-dimensional integral, we propose an importance sampling approach based on Monte Carlo random calculation. Next, an importance function is derived, which can simplify the problem of generating random vector from a high-dimensional probability density function (PDF) to generate random variable from a one-dimensional PDF. Compared with the existing maximum likelihood (ML) algorithms for DOA estimation of ID sources, the proposed algorithm does not require initial estimates, and its performance is closer to Cramer-Rao lower bound (CRLB). The proposed algorithm performs better than the existing methods when the interval between sources to be estimated is small and in low signal to noise ratio (SNR) scenarios.

Key words: direction-of-arrival (DOA) estimation, incoherently distributed (ID) sources, importance sampling maximum likelihood (ISML), Monte Carlo random calculation

Tao WU, Zhenghong DENG, Xiaoxiang HU, Ao LI, Jiwei XU. DOA estimation of incoherently distributed sources using importance sampling maximum likelihood[J]. Journal of Systems Engineering and Electronics, 2022, 33(4): 845-855.

Figures/Tables 9

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References 43

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Method	Average computing time	Relative speed
ESPRIT-like [14]	0.0101	1.00
ML1 [27]	0.1430	14.16
ML2 [28]	0.0970	9.60
Proposed method	0.1550	15.35

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DOA estimation of incoherently distributed sources using importance sampling maximum likelihood

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