• DocumentCode
    3578399
  • Title

    Sparse representation-based method for two-dimensional direction-of-arrival estimation with L-shaped array

  • Author

    Xiaoyu Luo ; Xiaochao Fei ; Ping Wei ; Lu Gan

  • Author_Institution
    Dept. of Electron. Eng., Univ. of Electron. Sci. & Technol. of China, Chengdu, China
  • fYear
    2014
  • Firstpage
    277
  • Lastpage
    280
  • Abstract
    A novel sparse representation-based method for two-dimensional (2-D) direction-of-arrival (DOA) estimation with L-shaped array is proposed. In our method, the 2-D DOA estimation is cast as a reconstituted problem of sparse matrix. The model for sparse-matrix reconstitution is first presented based on the cross-correlation matrix. Then an extended orthogonal matching pursuit (EOMP) algorithm is put forward to reconstitute the sparse matrix. With the use of the model for sparse-matrix reconstitution and EOMP algorithm, pair matching is no longer required in our method, and the estimation accuracy of our method is higher than the existing subspace-based and sparse representation-based methods. The simulation results demonstrate the effectiveness and efficiency of the proposed method.
  • Keywords
    array signal processing; correlation methods; direction-of-arrival estimation; iterative methods; signal representation; sparse matrices; time-frequency analysis; 2D DOA estimation; EOMP algorithm; L-shaped array; cross-correlation matrix; extended orthogonal matching pursuit algorithm; pair matching; sparse matrix reconstitution; sparse representation-based method; subspace-based method; two-dimensional direction-of-arrival estimation; Arrays; Azimuth; Direction-of-arrival estimation; Estimation; Sparse matrices; Transmission line matrix methods; Vectors;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Communication Problem-Solving (ICCP), 2014 IEEE International Conference on
  • Print_ISBN
    978-1-4799-4246-6
  • Type

    conf

  • DOI
    10.1109/ICCPS.2014.7062272
  • Filename
    7062272