Acoustic source tracking in a reverberant environment using a pairwise synchronous microphone network

This paper considers acoustic source tracking in a room environment using a distributed microphone pair network. Existing time-delay of arrival (TDOA) based approaches usually require all received signals to be transmitted to central processor and synchronized to extract the TDOA measurements. The source positions are then obtained by using a subsequent localization or tracking approach. In this paper, we propose a distributed particle filtering (PF) approach to track the source using a microphone pair network. Each node is constructed by a microphone pair and TDOA measurements are extracted at local nodes. An extended Kalman filter based PF is developed to estimate the first order and the second order statistics of the source state. A consensus filter is then applied to fuse these local statistics between neighboring nodes to achieve a global estimation. Under such an approach, only the state statistics need to be transmitted and the received signals need only to be pairwise synchronized. Consequently, both communication and computational cost can be significantly reduced. Simulations under different reverberant environments demonstrate that the proposed approach outperforms the centralized sequential importance sampling based PF approach in single source tracking as well as in non-concurrent multiple source tracking.