Systems Engineering and Electronics ›› 2018, Vol. 40 ›› Issue (4): 733-738.doi: 10.3969/j.issn.1001-506X.2018.04.03

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Joint cross covariance matrix based fast direction of arrival estimation

YAN Fenggang1, RONG Jiajia1, LIU Shuai1, SHEN Yi2, JIN Ming1   

  1. 1. School of Information and Electrical Engineering, Harbin Institute of Technology (Weihai), Weihai 264209, China;
    2. School of Electronics and Information Engineering, Harbin Institute of Technology, Harbin 150001, China
  • Online:2018-03-25 Published:2018-04-02

Abstract:

For the sake of reducing computation complexity caused by the subspace decomposition step in most of the state of the art subspace based algorithms for direction-of-arrival (DOA) estimation, a joint crosscovariance matrix (JCCM) based algorithm is proposed using a uniform linear array (ULA). Based on the ideas of array division and matrix remodeling, the ULA is divided into two subarrays, and two crosscovariance matrices are computed by the received datum of the two subarrays, with which a JCCM matrix is further reconstructed. Combing those three matrices, an equivalent signal subspace is found by conducting some lowcomplexity linear operations, and a polynomial is finally constructed to estimate source DOA without subspace decomposition. Theoretical analysis and simulation results show that the proposed technique can provide acceptable performances with the computational complexity effectively reduced and the faster estimation speed achieved.

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