Alpha-beta filter based target tracking in clustered wireless sensor networks

Abstract

The emerging field of wireless sensor networks (WSNs) allows novel methods of designing surveillance and tracking systems. Tracking moving targets in WSNs is a canonical application of practical importance to military as well as civilian fields. Since WSNs are highly constrained in computation, communication and energy resources, the application is required to be designed with minimal resource consumption. The collaborative and distributed approach in WSN is suited for effective utilization of scarce resources. In this paper, a Hierarchical Clustered network architecture has been considered for target tracking. A computationally simple predictive target tracking approach using α-β filter is proposed, evaluated and compared against a Kalman filter based approach.