Abstract
Sensor localisation and tracking is an important research topic in sensor networks. Collaboration of resource-constrained sensor nodes is extremely important to achieving substantial sensing and processing capability in the aggregate and to providing collectively reliable network behaviour in mission-critical applications. We propose a collaborative multi-sensor tracking (CMST) method for sensor networks and demonstrate through posterior Cramer-Rao bound (PCRB) analysis that sensors' mobility and collaboration can be exploited to significantly improve sensor localisation performance. We also propose a novel adaptive particle filtering algorithm AP-RPF and demonstrate its superior performance through simulation results.
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