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[Author] Zhi ZHENG(2hit)

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  • Parameter Estimation of Coherently Distributed Noncircular Signals

    Xuemin YANG  Zhi ZHENG  Guangjun LI  

     
    PAPER-Antennas and Propagation

      Vol:
    E98-B No:7
      Page(s):
    1316-1322

    In this paper, a new parameter estimator for coherently distributed (CD) noncircular (NC) signals is proposed, and can estimate both the central direction-of-arrivals (DOAs) and the angular spreads. It can also be considered as an extended version of the generalized Capon method by using both covariance matrix and an elliptic covariance matrix. The central DOAs and angular spreads are obtained by two-dimensional spectrum-peak searching. Numerical examples illustrate that the proposed method can estimate the central DOAs and the angular spreads when the number of signals is greater than the number of sensors. The proposed method also offers better performance than the methods against which it is compared.

  • 2-D DOA Estimation of Multiple Signals Based on Sparse L-Shaped Array

    Zhi ZHENG  Yuxuan YANG  Wen-Qin WANG  Guangjun LI  Jiao YANG  Yan GE  

     
    PAPER-DOA Estimation

      Pubricized:
    2017/08/22
      Vol:
    E101-B No:2
      Page(s):
    383-391

    This paper proposes a novel method for two-dimensional (2-D) direction-of-arrival (DOA) estimation of multiple signals employing a sparse L-shaped array structured by a sparse linear array (SLA), a sparse uniform linear array (SULA) and an auxiliary sensor. In this method, the elevation angles are estimated by using the SLA and an efficient search approach, while the azimuth angle estimation is performed in two stages. In the first stage, the rough azimuth angle estimates are obtained by utilizing a noise-free cross-covariance matrix (CCM), the estimated elevation angles and data from three sensors including the auxiliary sensor. In the second stage, the fine azimuth angle estimates can be achieved by using the shift-invariance property of the SULA and the rough azimuth angle estimates. Without extra pair-matching process, the proposed method can achieve automatic pairing of the 2-D DOA estimates. Simulation results show that our approach outperforms the compared methods, especially in the cases of low SNR, snapshot deficiency and multiple sources.