Maneuvering Target Tracking in Wireless Sensor Network with Range Only Measurement

Abstract

Abstract In this paper, we consider the condition of range-only measurement, and propose a novel maneuvering target algorithm in wireless sensor network (WSN) that can estimate the position and velocity of the target. Our algorithm combines maximum likelihood estimation and interacting multiple model filtering. Based on range information that the sensors measured, we use maximum likelihood method with constraint information to estimate the position, and then adopt interacting multiple model filtering to further improve the tracking accuracy. Simulation results shows that our algorithm can track maneuvering target effectively in wireless sensor network when we can obtain only range information.