• DocumentCode
    2334706
  • Title

    SPC10-4: EM Algorithm for Multiple Wideband Source Localization

  • Author

    Mada, Kiran K. ; Wu, Hsiao-Chun

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Commun. & Signal Processing Lab., Louisiana State Univ., Baton Rouge, LA
  • fYear
    2006
  • fDate
    Nov. 27 2006-Dec. 1 2006
  • Firstpage
    1
  • Lastpage
    5
  • Abstract
    A computationally efficient algorithm for multiple source localization, using the expectation-maximization (EM) algorithm, for the wideband sources in the near field of a sensor array/area, is presented. The basic idea is to decompose the observed sensor data, which is a superimposition of multiple sources, into individual components in the frequency domain and then estimate the corresponding location parameters associated with each component separately. Instead of the conventional alternating projection method, we propose to adopt the EM algorithm in this paper; our method involves two steps, namely Expectation (E-step) and Maximization (M-step). In the E-step, the individual incident source waveforms are estimated. Then, in the M-step, the maximum likelihood estimates of the source location parameters are obtained. These two steps are executed iteratively and alternatively until the pre-defined convergence is reached. The computational complexity comparison between our proposed EM algorithm and the existing alternating projection scheme is investigated. It is shown through Monte Carlo simulations that the computational complexity of the proposed EM algorithm is significantly lower than that of the conventional alternating projection algorithm.
  • Keywords
    Monte Carlo methods; array signal processing; computational complexity; direction-of-arrival estimation; expectation-maximisation algorithm; EM Algorithm; Monte Carlo simulations; computational complexity; direction-of-arrival estimation; expectation-maximization algorithm; individual incident source waveforms; maximum likelihood estimation; multiple wideband source localization; sensor array; sensor data; signal processing; Computational complexity; Convergence; Frequency domain analysis; Frequency estimation; Iterative algorithms; Maximum likelihood estimation; Position measurement; Projection algorithms; Sensor arrays; Wideband;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Global Telecommunications Conference, 2006. GLOBECOM '06. IEEE
  • Conference_Location
    San Francisco, CA
  • ISSN
    1930-529X
  • Print_ISBN
    1-4244-0356-1
  • Electronic_ISBN
    1930-529X
  • Type

    conf

  • DOI
    10.1109/GLOCOM.2006.589
  • Filename
    4151219