Tracking of multidimensional TDOA for multiple sources with distributed microphone pairs

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.

► We present a new framework for tracking multidimensional TDOA at distributed microphone pairs when several acoustic sources are active.
► A probabilistic tracking scheme is adopted based on a hybrid disjoint particle filters method implementing a track-before-detect strategy.
► Likelihoods are extracted from the recorded signals using an enhanced version of the GSCT.
► Observations are based either on the propagation time-delay estimated using the ICA or employing the phase of the cross-power spectrum.
► Experimental results are provided using simulated as well as real data.