78 / 2019-12-13 10:24:00
Augmented Quaternion MUSIC Method for a Uniform/Sparse COLD Array
全文被拒
Hua Chen / Ningbo University, China
Tianyi Zhao / Ningbo University, China
Weifeng Wang / Tianjin University, China
Qing Wang / Tianjin University, China
Gang Wang / Ningbo University, China
Wei-Ping Zhu / Concordia University, Canada
The quaternion multiple signal classification (Q-MUSIC) algorithm reduce the dimension of covariance matrix, which would result in performance degrading of DOA estimation. An augmented quaternion MUSIC algorithm (AQ-MUSIC) based on concentered orthogonal loop and dipole (COLD) array is presented in this paper. The proposed algorithm uses an augmented quaternion formalism to model the completely polarized signals, which allows a concise and novel way to an augmented covariance matrix. The fact reveals that the more accurate DOA parameters could be extracted from an augmented covariance matrix. Even compared with the long vector MUSIC (LV-MUSIC) algorithm whose dimension of covariance matrix is the same as AQ-MUSIC, the accuracy of DOA parameter estimation also is improved. Simulation results verify the performance promotion of the proposed approach.
重要日期
  • 会议日期

    06月08日

    2020

    06月11日

    2020

  • 01月12日 2020

    初稿截稿日期

  • 04月15日 2020

    提前注册日期

  • 12月31日 2020

    注册截止日期

主办单位
IEEE Signal Processing Society
承办单位
Zhejiang University
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