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Joint 2D-DOD and 2D-DOA Estimation for Coprime EMVS–MIMO Radar

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Abstract

The issue of two-dimensional (2D) direction-of-departure and direction-of-arrival estimation for bistatic multiple-input multiple-output (MIMO) radar with a coprime electromagnetic vector sensor (EMVS) is addressed in this paper, and a tensor-based subspace algorithm is proposed. Firstly, the covariance measurement of the received data is arranged into a fourth-order tensor, which can maintain the multi-dimensional characteristic of the received data. Then, the higher-order singular value decomposition is followed to get an accurate signal subspace. By utilizing the uniformity of the subarrays in coprime EMVS–MIMO radar, the rotation invariant technique is adopted to achieve ambiguous elevation angle estimation. Thereafter, the unambiguous elevation angles are recovered by exploring the coprime characteristic of the subarrays. Finally, all azimuth angles are achieved by using the vector cross-product strategy. The tensor nature inherited from the array measurement is fully explored, and the coprime geometry enables EMVS–MIMO radar to achieve larger array aperture than the existing uniform linear configuration; thus, the proposed method offers better estimation performance than current state-of-the-art algorithms. Several computer simulations validate the effectiveness of the proposed algorithm.

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Acknowledgements

This work is supported by the Key Research and Development Program of Hainan Province No. ZDYF2019011, the National Natural Science Foundation of China Nos. 61701144, 61801076, 61861015, and 61961013, the Program of Hainan Association for Science and Technology Plans to Youth R&D Innovation No. QCXM201706, the Scientific Research Projects of the University in Hainan Province No. Hnky2018ZD-4, Young Elite Scientists Sponsorship Program by CAST No. 2018QNRC001, Collaborative Innovation Fund of Tianjin University and Hainan University No. HDTDU201906, and the Scientific Research Setup Fund of Hainan University No. KYQD(ZR)1731.

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Authors and Affiliations

  1. State Key Laboratory of Marine Resource Utilization in South China Sea and School of Information and Communication Engineering, Hainan University, Haikou, 570228, China

    Xianpeng Wang & Mengxing Huang

  2. Key Laboratory for Ubiquitous Network and Service Software of Liaoning Province, School of Software, Dalian University of Technology, Dalian, 116620, China

    Liangtian Wan

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  1. Xianpeng Wang
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  2. Mengxing Huang
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Correspondence to Xianpeng Wang.

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Wang, X., Huang, M. & Wan, L. Joint 2D-DOD and 2D-DOA Estimation for Coprime EMVS–MIMO Radar. Circuits Syst Signal Process 40, 2950–2966 (2021). https://doi.org/10.1007/s00034-020-01605-5

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