Particle Filtering for Target Tracking with Mobile Sensors

Abstract

Recent progress in distributed robotics and low power embedded systems has led to development of mobile sensor networks. Controlled mobility, moving sensors intentionally, enables a new set of possibilities in wireless sensor networks and facilitates many applications in signal processing areas such as target tracking. In this paper we consider the problem of tracking a target using three mobile sensors that measure the received signal strength (RSS) from the target. We propose the use of particle filtering where the positioning of the mobile sensor is based on the predicted target's positions. In deciding how to deploy the sensors, we have used the Cramer-Rao lower bound (CRLB) that we have derived for our scheme. The performance of the method is investigated by simulations and compared to tracking by traditional static sensor network.