Target tracking system using lateration estimation method in wireless sensor networks

A tracking system can track a moving target, report to the Base Station (BS) and predict the wake-up zone while considering the trade-off between energy consumption and the accuracy of tracking performance. To estimate and predict the trajectory of a dynamic target, the use of Bayesian filter, Kalman filter and its derivations are proposed in [1]. The implementation of these different filters for a tracking system is also analysed. In this paper, we propose a new method to estimate the trajectory of a target: Lateration estimation. We then continue to simulate and analyse the performance of this method and compare to extended Kalman filter (EKF) in term of residual energy and tracking accuracy. Simulation results show that the Lateration estimation method can achieve better energy consumption while maintaining reasonable tracking performance.