author =    {Eric A. Lehmann and Darren B. Ward and Robert C. Williamson},
  title =     {Experimental comparison of particle filtering algorithms for acoustic source localization in a reverberant room},
  booktitle = {Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP'03)},
  volume =    {5},
  pages =     {177--180},
  month =     {April},
  year =      {2003},
  address =   {Hong Kong, China},
  note =      {This paper was presented at the IEEE Workshop on Applications of Signal Processing to Audio and Acoustics (WASPAA'03), New Paltz, New York, October 2003},
  abstract =  {Traditional acoustic source localization techniques attempt to determine the current location of an acoustic source from data obtained at an array of sensors during the current time only. Recently, state-space methods have been proposed that use particle filters to perform recursive estimation of the current source location using all previous data. In this paper we present an overview of these particle filter algorithms, and formulate performance measures for determining their ability to track a moving source. We present results of experiments using reverberant data recorded in a real room, and show that steered beamforming methods have improved performance over GCC-based approaches.}