Journal of Systems Engineering and Electronics ›› 2021, Vol. 32 ›› Issue (4): 756-763.doi: 10.23919/JSEE.2021.000065

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A search-free near-field source localization method with exact signal model

Jingjing PAN1,2(), Parth Raj SINGH3(), Shaoyang MEN4,*()   

  1. 1 Key Laboratory of Dynamic Cognitive System of Electromagnetic Spectrum Space, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China
    2 Department of Electronic Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China
    3 International Electronics Engineering S.A., Bissen L-7795, Luxembourg
    4 School of Medical Information Engineering, Guangzhou University of Chinese Medicine, Guangzhou 510006, China
  • Received:2020-11-24 Online:2021-08-18 Published:2021-09-30
  • Contact: Shaoyang MEN E-mail:jingjingpan@nuaa.edu.cn;parth-raj.singh@iee.lu;shaoyang.men@gzucm.edu.cn
  • About author:|PAN Jingjing was born in 1991. She received her B.S. and M.S. degrees in cartography and geographic information science from East China Normal University and Beijing Normal University, in 2012 and 2015, respectively. In 2019, she received her Ph.D. degree in electronic systems and radar signal processing from Polytech Nantes, University of Nantes, France. She is now a postdoctoral fellow in Department of Electronic Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing, China. Her research interests include array signal processing and nondestructive testing.E-mail: jingjingpan@nuaa.edu.cn||SINGH Parth Raj was born in 1989. He received his M.S. and Ph.D. degrees in electronic systems and radar signal processing from Polytech Nantes, University of Nantes, in 2014 and 2017, respectively. He is currently an engineer at International Electronics Engineering S.A., Bissen, Luxembourg. His research interests include array signal processing and vital sign monitoring systems.E-mail: parth-raj.singh@iee.lu||MEN Shaoyang was born in 1988. He received his M.S. degree in electronic systems and radar signal processing from Polytech Nantes, University of Nantes, France, in 2013, and M.S. degree in communication and information system from South China University of Technology, Guangzhou, China, in 2014. In 2016, he received his Ph.D. degree in digital communications systems from Polytech Nantes, University of Nantes, France. He has been an assistant professor with Guangzhou University of Chinese Medicine, China, since 2017. His current research interests include array signal processing, cognitive wireless sensor networks, and medical image processing.E-mail: shaoyang.men@gzucm.edu.cn
  • Supported by:
    This work was supported by the Key Laboratory of Dynamic Cognitive System of Electromagnetic Spectrum Space (KF20202109), the National Natural Science Foundation of China (82004259), and the Young Talent Training Project of Guangzhou University of Chinese Medicine (QNYC20190110)

Abstract:

Most of the near-field source localization methods are developed with the approximated signal model, because the phases of the received near-field signal are highly non-linear. Nevertheless, the approximated signal model based methods suffer from model mismatch and performance degradation while the exact signal model based estimation methods usually involve parameter searching or multiple decomposition procedures. In this paper, a search-free near-field source localization method is proposed with the exact signal model. Firstly, the approximative estimates of the direction of arrival (DOA) and range are obtained by using the approximated signal model based method through parameter separation and polynomial rooting operations. Then, the approximative estimates are corrected with the exact signal model according to the exact expressions of phase difference in near-field observations. The proposed method avoids spectral searching and parameter pairing and has enhanced estimation performance. Numerical simulations are provided to demonstrate the effectiveness of the proposed method.

Key words: near-field, source localization, polynomial rooting, approximation error, exact signal model