Tracking of multidimensional TDOA for multiple sources with distributed microphone pairs

Abstract

This paper presents a general framework for tracking the time differences of arrivals of multiple acoustic sources recorded by distributed microphone pairs. Tracking is based on a three-stage analysis. Complex-valued propagation models are extracted at different time instants and frequencies using either the independent component analysis or the phase of the cross-power spectrum evaluated at each microphone pair. In both cases, approximated densities of the propagation time delays are derived through the generalized state coherence transform. A sequential Bayesian tracking scheme with an integrated activity detection is finally implemented through disjoint particle filters based on a track-before-detect strategy. Experiments on both synthetic and real data recorded by two distributed microphone pairs show that the proposed framework can detect and track up to five sources simultaneously active in a reverberant environment.