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Unitary Subspace-Based Method for Angle Estimation in Bistatic MIMO Radar

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Abstract

In this paper, the issue of joint angle estimation for bistatic multiple-input multiple-output (MIMO) radar is investigated, and an algorithm for the joint estimation under real-valued computation is proposed. By utilizing the unitary transformation, the direction matrices and the data matrix are transformed to be real-valued ones. The direction of departure (DOD) can be estimated via the real-valued rotational invariance in the subspace, and the direction of arrival (DOA) can be obtained via the real-valued reduced-dimension function of multiple signal classification (MUSIC). The proposed algorithm utilizes both the signal and noise subspaces, requires no peak searching, and can achieve automatically paired estimations of the angles. Furthermore, it has better angle estimation performance than some existing methods. The simulation results verify the algorithmic effectiveness and robustness of the proposed algorithm.

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Acknowledgements

This work is supported by China NSF Grants (61201208, 61271327, 61071164), Jiangsu Planned Projects for Postdoctoral Research Funds (1201039C), the China Postdoctoral Science Foundation (2012M521099), the Hubei Key Laboratory of Intelligent Wire1ess Communications (IWC2012002), the Open project of the Key Laboratory of Nondestructive Testing (Nanchang Hangkong University), the Aeronautical Science Foundation of China (20120152001), the Qing Lan Project, Research Innovation Program for College Graduates of Jiangsu Province (CXZZ13_0165), Funding for Outstanding Doctoral Dissertation in NUAA (BCXJ13-09), PAPD of Jiangsu Higher Education Institutions, and the Fundamental Research Funds for the Central Universities (NS2013024, NZ2012010, kfjj120115, kfjj20110215).

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Authors and Affiliations

  1. College of Electronic and Information Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing, Jiangsu, 210016, China

    Jianfeng Li & Xiaofei Zhang

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  1. Jianfeng Li
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  2. Xiaofei Zhang
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Correspondence to Jianfeng Li.

Appendix

Appendix

Define h t=−angle(a r (ϕ k )), which contains the ambiguous phases. Set the initial elements of h as zeros. The unambiguous phases can be identified via the following two steps [19].

  1. 1.

    Set the first element: h(1)=0.

  2. 2.

    h(n+1)=h(n)+δ(n),n=1,…,N−1 where

    $$ \delta ( n ) = \left \{ \begin{array}{l@{\quad}l} \mathbf{h}^{t} ( n + 1 ) - \mathbf{h}^{t} ( n ) & \bigl\vert \mathbf{h}^{t} ( n + 1 ) - \mathbf{h}^{t} ( n ) \bigr\vert \le \pi\\ \mathbf{h}^{t} ( n + 1 ) - \mathbf{h}^{t} ( n ) - 2\pi & \mathbf{h}^{t} ( n + 1 ) - \mathbf{h}^{t} ( n ) > \pi \\ \mathbf{h}^{t} ( n + 1 ) - \mathbf{h}^{t} ( n ) + 2\pi & \mathbf{h}^{t} ( n + 1 ) - \mathbf{h}^{t} ( n ) < \pi \end{array} \right .$$

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Li, J., Zhang, X. Unitary Subspace-Based Method for Angle Estimation in Bistatic MIMO Radar. Circuits Syst Signal Process 33, 501–513 (2014). https://doi.org/10.1007/s00034-013-9653-9

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