Energy Efficient Policies for Distributed Target Tracking in Multihop Sensor Networks

We consider the problem of distributed target tracking in a sensor network under communication constraints between the sensor nodes, a problem that has recently received significant attention. The problem requires the dynamic selection of which sensor nodes will communicate their information and the selection of a corresponding fusion center which will process the collected information. Ideally, selection of which sensors will communicate and where will fusion take place will be a dynamic process, adapting to new information, to trade off tracking accuracy versus communications usage. The resulting coupled problem is generally intractable and significant effort has been devoted towards proposing simple strategies under various performance criteria. In this paper, we propose an adaptive dynamic strategy for sensor selection and fusion location using a certainty equivalence approach that seeks to optimize a tradeoff between tracking error and communications cost. We define a certainty equivalent optimization problem for dynamic relocation of the fusion center that uses measures of average multi hop communications cost and average tracking errors, and solve the resulting optimal control problem for classes of tracking problems. The optimal strategy is a hybrid switching strategy, where the fusion center location and reporting sensors are held stationary unless the target estimates move outside of a threshold radius around the sensors. We illustrate the performance of our algorithms on sample tracking experiments with sensor networks