Range-free passive acoustic localization

We propose a range-free localization framework in which a network of randomly deployed acoustic sensors can passively use natural acoustic phenomena within its environment to localize itself. We introduce a novel approach for registration of sensors observations which takes advantage of a clustering technique on triplets of associated observations. A Bayesian filtering method is employed to incrementally improve system state estimation as more observations become available. To the best of our knowledge this is the first work done on range-free passive acoustic localization. Simulation experiments of the proposed algorithms are presented.