An Efficient Sensor Scheduling for Target Tracking

In this article, an efficient sensor scheduling is proposed which is an interesting issue by applying wireless sensor network (WSN) for addressing to track a mobile target. The proposed efficient and simple algorithm is mainly for assisting mobile sensors management that is deployed in tracking a considerable moving target. The presented novel method leads to minimize comparison number of sensor sequences and to reduce executive time for unconstrained optimization. Moreover, the simulation results show that it is in reduction of memory utilization, energy consumption and computational cost as well. The famous Kalman Filter technique was applied to estimate posteriori state of the target in order to minimize mean square error (MSE) value in prediction step. In addition, the propagation channel is assumed as additive white Gaussian noise (AWGN) model for significant the contribution. Numerical example reveals that the developed algorithm can obtain an optimal scheduling outcome by an easy implementation.