RESOURCE CONSTRAINED EFFICIENT ACOUSTIC SOURCE LOCALIZATION AND TRACKING USING A DISTRIBUTED NETWORK OF MICROPHONES

In this paper we present an efficient method to perform acoustic source localization and tracking using a distributed network of mi-crophones. In this scenario, there is a trade-off between the local-ization performance and the expense of resources: in fact, a mini-mization of the localization error would require to use as many sen-sors as possible; at the same time, as the number of microphones increases, the cost of the network inevitably tends to grow, while in practical applications only a limited amount of resources is avail-able. Therefore, at each time instant only a subset of the sensors should be enabled in order to meet the cost constraints. We propose a heuristic method for the optimal selection of this subset of micro-phones, using as distortion metrics the Cramer-Rao Lower Bound (CRLB) and as cost function the total distance between the selected sensors. The heuristic approach has been compared to an optimal algorithm, which searches the best sensor configuration among the full set of microphones, while satisfying the cost constraint. The proposed heuristic algorithm yields similar performance w.r.t. the full-search procedure, but at a much less computational cost. We show that this method can be used effectively in an acoustic source tracking application