Adaptive sampling with sensor selection for target tracking in wireless sensor networks

In this paper, we consider a target tracking problem where the time interval between adjacent sensor measurements is a decision variable to be optimized. Therefore, we aim to sample the target very frequently when the uncertainty is large and sample the target less frequently when the uncertainty is small. Having obtained when to sample the target, next we determine which sensors to be selected at the intended sampling instant. Simulation results show that the proposed algorithm provides similar estimation performance to the algorithm where all sensors transmit with fixed and small sampling intervals. Moreover, adaptive sampling with sensor selection provides significant savings on the number of sensors selected in the entire tracking period as compared to fixed target sampling case.