Target Tracking under Uncertainty in Wireless Sensor Networks

Target tracking is a well studied topic in wireless sensor networks. However, uncertainty existed in sensor networks presents new challenges for it. Besides the energy conservation of networks, target tracking has to deal with different kinds of uncertainty, such as the impreciseness of positioning systems, environment noise and limited sensitivity of sensors. In this paper, we study the problem of target tracking under uncertainty in wireless sensor networks. We first investigate the uncertainty existed in sensor networks and propose a series of general models. Then, we introduce the problem of probabilistic k-nearest neighbors (PkNN) and provide an efficient tracking algorithm based on PkNN retrieval under the proposed models. Finally, a comprehensive set of simulations are presented. We conclude that the proposed tracking algorithm yields excellent tracking performance in wireless sensor networks.