Target tracking of binary wireless sensor networks in the domain of medicine and healthcare

Abstract

In the domain of medicine and healthcare (M&HC), wireless sensor networks (WSNs) play a more and more important role. Under some special situations, the object of the WSN is moving leading to the problems of target tracking. Since real–time and communication amount is crucial for the WSN target tracking, the performance of target tracking in the WSN is critically depended on real–time and communication amount reduction. This paper presents a target tracking method based on distributed adaptive particle filtering in binary WSN. On the basis of dynamic clustering, the adaptive particle filter receives the observations from children nodes and formulates the local estimate with the cluster head as the processing centre. Simulation results show that the method can effectively improve the real–time tracking and reduce communication amount.