Weighted Distance Based Sensor Selection for Target Tracking in Wireless Sensor Networks

Abstract

A novel weighted distance based node selection method for bearings-only sensors in wireless sensor networks (WSN) is proposed. Weighted distance is involved as information utility in sensor management of WSN. Based on the probability distribution function of predicted target state and the bearing error of a sensor itself, the sensor with the minimum weighted distance is activated in the tracking mission. Compared with entropy based method, the proposed method saves much computational cost by avoiding the estimation of the posteriori distribution. Simulation results demonstrated that the proposed method can achieve competitive tracking accuracy comparing to the existing representative methods.