• DocumentCode
    3594677
  • Title

    Fast Bayesian acoustic localization

  • Author

    Birchfield, Stanley T. ; Gillmor, Daniel Kahn

  • Author_Institution
    Quindi Corporation, 480 S. California Ave., Palo Alto, 94306, USA
  • Volume
    2
  • fYear
    2002
  • Abstract
    We derive a probabilistic formulation, based upon Bayes´ rule, for the acoustic localization problem. The resulting formula is shown to be closely related to the energy of a conventionally beamformed signal. We then present a close approximation to both which is much faster to compute — by two orders of magnitude with our experimental setup. The fast algorithm is essentially a generalization of approaches based upon time delay estimates (TDE´s), by applying the principle of least commitment. Experiments on real signals demonstrate accurate localization in noisy, reverberant environments (less than 3 dB SNR) several times faster than real time.
  • Keywords
    Array signal processing; Artificial intelligence; Filtering; Microphones; Signal to noise ratio;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Acoustics, Speech, and Signal Processing (ICASSP), 2002 IEEE International Conference on
  • ISSN
    1520-6149
  • Print_ISBN
    0-7803-7402-9
  • Type

    conf

  • DOI
    10.1109/ICASSP.2002.5744971
  • Filename
    5744971