• DocumentCode
    1928883
  • Title

    Particle filter based DOA estimation for multiple source tracking (MUST)

  • Author

    Wiese, Thomas ; Claussen, Heiko ; Rosca, Justinian

  • Author_Institution
    Sch. of Electr. Eng., Tech. Univ. Munich, Munich, Germany
  • fYear
    2011
  • fDate
    6-9 Nov. 2011
  • Firstpage
    624
  • Lastpage
    628
  • Abstract
    Direction of arrival estimation is a well researched topic and represents an important building block for higher level interpretation of data. The Bayesian algorithm proposed in this paper (MUST) can estimate and track the direction of multiple, possibly correlated, wideband sources. MUST approximates the posterior probability density function of the source directions in time-frequency domain with a particle filter. In contrast to other previous algorithms, no time-averaging is necessary, therefore moving sources can be tracked. MUST uses a new low complexity weighting and regularization scheme to fuse information from different frequencies and to overcome the problem of overfitting when few sensors are available.
  • Keywords
    Bayes methods; direction-of-arrival estimation; particle filtering (numerical methods); Bayesian algorithm; MUST; direction-of-arrival estimation; multiple source tracking; particle filter based DOA estimation; posterior probability density function; regularization scheme; time-frequency domain; Arrays; Bayesian methods; Direction of arrival estimation; Estimation; Noise; Sensors;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Signals, Systems and Computers (ASILOMAR), 2011 Conference Record of the Forty Fifth Asilomar Conference on
  • Conference_Location
    Pacific Grove, CA
  • ISSN
    1058-6393
  • Print_ISBN
    978-1-4673-0321-7
  • Type

    conf

  • DOI
    10.1109/ACSSC.2011.6190077
  • Filename
    6190077