Integrated detection and tracking of multiple objects with a network of acoustic sensors

The problem is joint detection and tracking of possibly several objects moving through a region of interest. A wireless sensor network (WSN), deployed in the region, collects the acoustic energy measurements and sends them to the fusion center for processing. The problem is cast in the sequential Bayesian estimation framework and solved using a particle filter. The number of objects is unknown and can vary over time. The paper presents the algorithm and demonstrates its performance by computer simulations. The particle filter error performance is compared to the theoretical Cramer-Rao bound (CRB) for multiple target tracking with the described WSN.