Distributed implementation of particle filters for collaborative tracking in mobile ad-hoc and sensor networks

Distributed particle filtering algorithms are studied in this paper for collaborative tracking in mobile ad-hoc and sensor networks. With collaborative tracking methods, multiple unknown location (UL) nodes are tracked simultaneously based on not only the measurements between UL nodes and reference nodes with known locations, but also the measurements among UL nodes. Thus, UL nodes can help one another to achieve better performance. We propose a distributed collaborative tracking algorithm with particle filters and study the performance through various simulations.