A hybrid localization approach in wireless sensor networks using a mobile beacon and inter-node communication

In this paper we propose a distributed approach for localization in wireless sensor networks using a mobile beacon based on Particle Filter (PF) and Extended Kalman Filter (EKF). The algorithm has two phases. In the first phase, each node localizes itself using messages received from the mobile beacon. In the second phase nodes cooperate with each other to improve their estimations of their locations. In the first phase particle filter is used for localization due to its multi-modal/multi-hypothesis nature. In the later EKF is used, due to the nonlinearity nature of the problem in hand, to improve the estimation. On the other hand, using EKF, instead of PF, in the inter-node communication reduces the communication bandwidth tremendously. The mobile beacon's trajectory is based on Hilbert curve which has shown better accuracy in localizing the nodes in the sensor network. The simulation results show better performance than the previous approaches, that either uses inter-node communication or mobile beacon localization.