Improving target tracking by incorporating shadowing fading

To accurately localize the target, wireless positioning systems use range measurements from different anchors, which are deployed around the monitored region in advance. In most applications where the target such as a human body has a certain volume, the target will shadow the wireless links comprised of the anchors, making the received signal strength (RSS) of these links suffer great loss. Therefore, in this paper, we propose a hybrid approach which integrates shadowing fading and range measurements of the links to enhance the performance of target tracking. Due to the nonlinearity of the shadowing loss model and the range model, particle filtering (PF) maximizing the posterior distribution of the target state is employed to fusion the two kinds of measurements. Moreover, the posterior Cramer-Rao lower bound (PCRLB) is derived to explore the best possible performance of the hybrid approach. Simulation results show that the tracking performance is significantly improved when the shadowing fading is exploited.