author =   {Darren B. Ward and Eric A. Lehmann and Robert C. Williamson},
  title =    {Particle filtering algorithms for tracking an acoustic source in a reverberant environment},
  journal =  {IEEE Transactions on Speech and Audio Processing},
  volume =   {11},
  number =   {6},
  pages =    {826--836},
  month =    {November},
  year =     {2003},
  abstract = {Traditional acoustic source localization algorithms attempt to find the current location of the acoustic source using data collected at an array of sensors at the current time only. In the presence of strong multipath, these traditional algorithms often erroneously locate a multipath reflection rather than the true source location. A recently proposed approach that appears promising in overcoming this drawback of traditional algorithms, is a state-space approach using particle filtering. In this paper we formulate a general framework for tracking an acoustic source using particle filters. We discuss four specific algorithms that fit within this framework, and demonstrate their performance using both simulated reverberant data and data recorded in a moderately reverberant office room (with a measured reverberation time of 0.39 s). The results indicate that the proposed family of algorithms are able to accurately track a moving source in a moderately reverberant room.}