• DocumentCode
    3421127
  • Title

    Doa estimation by covariance matrix sparse reconstruction of coprime array

  • Author

    Chengwei Zhou ; Zhiguo Shi ; Yujie Gu ; Goodman, Nathan A.

  • Author_Institution
    Dept. of ISEE, Zhejiang Univ., Hangzhou, China
  • fYear
    2015
  • fDate
    19-24 April 2015
  • Firstpage
    2369
  • Lastpage
    2373
  • Abstract
    In this paper, we propose a direction-of-arrival estimation method by covariance matrix sparse reconstruction of coprime array. Specifically, source locations are estimated by solving a newly formulated convex optimization problem, where the difference between the spatially smoothed covariance matrix and the sparsely reconstructed one is minimized. Then, a sliding window scheme is designed for source enumeration. Finally, the power of each source is re-estimated as a least squares problem. Compared with existing methods, the proposed method achieves more accurate source localization and power estimation performance with full utilization of increased degrees of freedom provided by coprime array.
  • Keywords
    covariance matrices; direction-of-arrival estimation; least squares approximations; optimisation; signal reconstruction; DOA estimation; convex optimization problem; coprime array; direction-of-arrival estimation; least squares problem; power estimation performance; source enumeration; source localization; source locations; sparse reconstruction; spatially smoothed covariance matrix; Arrays; Conferences; Covariance matrices; Direction-of-arrival estimation; Estimation; Sparse matrices; Compressive sensing; coprime array; direction-of-arrival estimation; power estimation; source localization;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Acoustics, Speech and Signal Processing (ICASSP), 2015 IEEE International Conference on
  • Conference_Location
    South Brisbane, QLD
  • Type

    conf

  • DOI
    10.1109/ICASSP.2015.7178395
  • Filename
    7178395