Investigation of Sensing Range for High Speed Target Tracking in Wireless Sensor Networks

In this paper, we propose a new approach for selection of subsets of active sensors with some constraints on energy consumption and estimation error for tracking of a target. The proposed approach exploits the decentralized estimation by using the extended information filter for target tracking. Furthermore, a cost function is defined using spatial correlation for sensor selection. Consequently, the Spatial Split algorithm is proposed based on spatial correlation coefficients for sensor selection. At last, for high speed targets, we propose a modification on spatial split algorithm by changing the sensing range with respect to the target speed. Simulation results show that the tracking accuracy is analogous to those of optimal estimation methods. It is also found that energy consumption decreases due to activating only necessary sensors.