Sequential acoustic energy based source localization using particle filter in a distributed sensor network

A sequential source localization method using a particle filter is presented to estimate and track multiple-target locations. This method is designed to make use of an acoustic signal measured at multiple acoustic sensors randomly deployed in a wireless distributed sensor network. By using the particle filter, a non-Gaussian probability density function of the target locations is represented by a discrete set of "particles". The positions of these particles are propagated sequentially using known state transition equation, and updated using new location estimates via the observation equation. Compared to a previously proposed maximum likelihood source localization algorithm, this new approach is computationally effective and more robust to parameter perturbation.