• DocumentCode
    190849
  • Title

    A fast DOA estimation algorithm based on subspace projection

  • Author

    Jingjing Cai ; Peng Li ; Yinping Zhang ; Guoqing Zhao

  • Author_Institution
    Key Lab. of Electron. Inf. Countermeasure & Simulation Technol. Minist. of Educ., Xidian Univ., Xian, China
  • fYear
    2014
  • fDate
    5-8 Aug. 2014
  • Firstpage
    199
  • Lastpage
    203
  • Abstract
    The Multiple Signal Classification (MUSIC) algorithm is a representative method for the Direction of Arrival (DOA) estimation. However, it has to compute Eigenvalue Decomposition (EVD) and cumulate certain snapshots for once DOA estimation, which is costly in the computation and limits its applications. This paper proposes a Subspace Projection based MUSIC (SP-MUSIC) algorithm. The algorithm avoids computing EVD in the subspace estimation. It reduces the computational complexity and need not cumulate snapshots. Moreover, a Simplified SP-MUSIC (SSP-MUSIC) is devised, which accelerates the DOA estimation further. The computation and memory usage for the both algorithms are analyzed theoretically. The computational complexities are reduced greatly, especially for the SSP-MUSIC. And the SSP-MUSIC also takes a smaller memory capacity. Through the simulations, it is illustrated that the performance of the SP-MUSIC and the SSP-MUSIC is quit close to the traditional MUSIC.
  • Keywords
    computational complexity; direction-of-arrival estimation; eigenvalues and eigenfunctions; signal classification; DOA estimation algorithm; EVD; MUSIC algorithm; SP-MUSIC algorithm; computational complexity reduction; direction of arrival estimation; eigenvalue decomposition; multiple signal classification algorithm; subspace estimation; subspace projection; Arrays; Computational complexity; Covariance matrices; Direction-of-arrival estimation; Eigenvalues and eigenfunctions; Estimation; Multiple signal classification; Direction of arrival (DOA); MUSIC; computational complexity; subspace projection;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Signal Processing, Communications and Computing (ICSPCC), 2014 IEEE International Conference on
  • Conference_Location
    Guilin
  • Print_ISBN
    978-1-4799-5272-4
  • Type

    conf

  • DOI
    10.1109/ICSPCC.2014.6986182
  • Filename
    6986182