Sensor selection for target tracking in WSN Using Modified INS algorithm

Regarding to densely deployment of sensors and information redundancy in wireless sensor networks (WSN), it may not be necessary for every sensor to be active at any time instant. In this paper, we present a new algorithm for selection of subsets of active sensors with some constraints on energy consumption and estimation error for tracking of a target. To do so, a decentralized estimation is incorporated using the extended information filter for target tracking and a cost function is defined using spatial correlation for sensor selection. This leads to introducing the modified iterative node selection (MINS) algorithm based on vector quantization for sensor selection. Simulation results show that not only tracking accuracy is analogous to optimal estimation methods, but also the estimation error is lower, and yet, energy consumption is decreased due to activating only necessary sensors.