Title :
Tracking Multiple Acoustic Sources in Reverberant Environments using Regularized Particle Filter
Author :
Antonacci, F. ; Matteucci, M. ; Migliore, D. ; Riva, D. ; Sarti, A. ; Tagliasacchi, M. ; Tubaro, S.
Author_Institution :
Politecnico di Milano, Milan
Abstract :
This paper concerns the problem of tracking acoustic sources in reverberant environments by using a particle filter. The localization problem is transformed into the retrieval of the unobservable state of a dynamical model through noisy measures. Though effective, two problems are related to particle filter: the degeneracy phenomenon (all particles but one are not significative) and the loss of diversity (all particles collapse on the same point). By using Regularized par ticle filter (RPF) and Expectation Maximization (EM) we propose a solution to both problems. Experimental results validate the pro posed solution: Regularized Particle Filter enables to obtain a RMS error lower than 0.2m with a reverberation time of 0.6s.
Keywords :
acoustic radiators; acoustic signal processing; expectation-maximisation algorithm; mean square error methods; particle filtering (numerical methods); tracking; RMS error; degeneracy phenomenon; expectation maximization algorithm; localization problem; multiple acoustic source tracking; regularized particle filter; reverberant environment; Acoustic measurements; Acoustic noise; Blind source separation; Clustering algorithms; Kalman filters; Particle filters; Particle tracking; Position measurement; Reverberation; State estimation; Blind Source Separation; Expectation Maximization; Particle filter; Regularized particle filter; Time Differences of Arrival;
Conference_Titel :
Digital Signal Processing, 2007 15th International Conference on
Conference_Location :
Cardiff
Print_ISBN :
1-4244-0882-2
Electronic_ISBN :
1-4244-0882-2
DOI :
10.1109/ICDSP.2007.4288528