• DocumentCode
    1752266
  • Title

    DOA estimation using fast EM algorithm

  • Author

    Chung, Pei Jung ; Bohme, Johann F.

  • Author_Institution
    Dept. of Electr. Eng. & Inf. Sci., Ruhr-Univ., Bochum, Germany
  • Volume
    1
  • fYear
    2001
  • fDate
    2001
  • Firstpage
    128
  • Abstract
    We study the direction of arrival estimation using expectation-maximization (EM) algorithm. The EM algorithm is a general and popular numerical method for finding maximum likelihood estimates which usually has a simple implementation and stable convergence. However, the computational cost caused by the slow convergence of the EM algorithm is still immense for the direction finding problem. Motivated by componentwise convergence of the EM algorithm, we suggest the use of smaller search spaces after a few iterations. In this way, the overall computational cost can be reduced drastically. An adaptive procedure which determines the search spaces involved in the maximization (M) step is proposed. With numerical experiments we demonstrate the improvement of the computational efficiency by using the proposed algorithm
  • Keywords
    array signal processing; convergence of numerical methods; direction-of-arrival estimation; maximum likelihood estimation; optimisation; search problems; DOA estimation; MLE; adaptive procedure; computational cost reduction; computational efficiency; direction finding problem; direction of arrival estimation; expectation-maximization algorithm; fast EM algorithm; maximum likelihood estimates; numerical experiments; search spaces; stable convergence; Computational complexity; Computational efficiency; Convergence of numerical methods; Costs; Direction of arrival estimation; Gaussian noise; Information science; Maximum likelihood estimation; Sensor arrays; Signal to noise ratio;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Signal Processing and its Applications, Sixth International, Symposium on. 2001
  • Conference_Location
    Kuala Lumpur
  • Print_ISBN
    0-7803-6703-0
  • Type

    conf

  • DOI
    10.1109/ISSPA.2001.949792
  • Filename
    949792