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Dec. 2021
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Article Navigation> JOURNAL OF BEIJING INSTITUTE OF TECHNOLOGY> 2021> 30(4): 352-362
Guanjun Huang, Yongquan Li, Zijing Zhang, Junpeng Shi, Fangqing Wen. Tensor-Based Source Localization Method with EVS Array[J]. JOURNAL OF BEIJING INSTITUTE OF TECHNOLOGY, 2021, 30(4): 352-362. doi: 10.15918/j.jbit1004-0579.2021.020
Citation: Guanjun Huang, Yongquan Li, Zijing Zhang, Junpeng Shi, Fangqing Wen. Tensor-Based Source Localization Method with EVS Array[J].JOURNAL OF BEIJING INSTITUTE OF TECHNOLOGY, 2021, 30(4): 352-362.doi:10.15918/j.jbit1004-0579.2021.020
shu

Tensor-Based Source Localization Method with EVS Array

doi:10.15918/j.jbit1004-0579.2021.020
  • 1.

    Department of Electronic and Information, Yangtze University, Jingzhou 434200, Hubei, China

  • 2.

    Department of National Laboratory of Radar Signal Processing, Xidian University, Xi’an 710071, China

  • 3.

    Department of Electronic Countermeasure, National University of Defense Technology, Hefei 230037, China

Funds:This work is supported by the National Natural Science Foundation of China (Nos. 61701046, 61871218 and 62071476).
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  • Author Bio:

    Guanjun Huangreceived the B.S. degree in electronic information engineering from Yangtze University in 2019. He is pursuing for a M.S. degree in Yangtze University, Jingzhou, China. His current research interests include array signal processing and multiple-input multiple-output radar parameter estimation

    Yongquan Ligraduated from Nanjing University of Aeronautics and Astronautics, Bachelor of engineering. He is an Associate professor and master supervisor of School of Electronic Information, Yangtze University. His main research interests are signal processing, information transmission and other directions

    Zijing Zhangwas born in Beijing, China, in 1967. He received the B.S. and M.S. degrees in dynamics from the Harbin Institute of Technology, Harbin, China, in 1989 and 1992, respectively, and the Ph.D. degree in electrical engineering from Xidian University, Xi’an, China, in 2001. From 2006 to 2006, he was a Visiting Scholar with The University of Manchester, Manchester, U.K. From 2016 to 2017, he was a Visiting Scholar with the University of Delaware, Newark, DE, USA. Since 1992, he has been with the National Laboratory of Radar Signal Processing, Xidian University, where he is a Professor. His research interests include radar signal processing and radar imaging

    Junpeng Shireceived the M.S. and Ph.D. degrees from Air Force Engineering University, Xi’an, China, in 2014 and 2018, respectively. He is currently a Lecturer in information and communication engineering with the National University of Defense Technology (NUDT), Hefei, China. His current research interest includes tensor signal processing with sparse MIMO radar

    Fangqing Wen(Member, IEEE) was born in Hubei, China, in 1988. He received the B.S. degree in electronic engineering from the Hubei University of Automotive Technology, Shiyan, China, in 2011, the master’s degree from the College of Electronics and Information Engineering, Nanjing University of Aeronautics and Astronautics (NUAA), China, in 2013, and the Ph.D. degree from NUAA, in 2016. From October 2015 to April 2016, he was a Visiting Scholar with the University of Delaware, USA. Since 2016, he has been with the Electronic and Information School, Yangtze University, China, where he is currently an Assistant Professor. His research interests include MIMO radar, array signal processing, and compressive sensing. He is a member of the Chinese Institute of Electronics (CIE). He is also an Associate Editor of the Electronics Letters journal

  • Corresponding author:Email: yqli.beijing@163.com
  • Received Date:2021-04-07
  • Rev Recd Date:2021-05-20
  • Accepted Date:2021-07-02
    • Available Online:2021-12-25
  • Publish Date:2021-12-27
    Abstract
  • In many wireless scenarios, e.g., wireless communications, radars, remote sensing, direction-of-arrival (DOA) is of great significance. In this paper, by making use of electromagnetic vector sensors (EVS) array, we settle the issue of two-dimensional (2D) DOA, and propose a covariance tensor-based estimator. First of all, a fourth-order covariance tensor is used to formulate the array covariance measurement. Then an enhanced signal subspace is obtained by utilizing the higher-order singular value decomposition (HOSVD). Afterwards, by exploiting the rotation invariant property of the uniform array, we can acquire the elevation angles. Subsequently, we can take advantage of vector cross-product technique to estimate the azimuth angles. Finally, the polarization parameters estimation can be easily completed via least squares, which may make contributions to identifying polarization state of the weak signal. Our tensor covariance algorithm can be adapted to spatially colored noise scenes, suggesting that it is more flexible than the most advanced algorithms. Numerical experiments can prove the superiority and effectiveness of the proposed approach.
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