A Localization and Tracking Approach with Sparse Reference Tags

In traditional localization systems, it is required that moving object carries a device to transmit or receive signals, and then localization system is able to locate an object based on signal strength it received. In this paper, we propose a new passive localization and tracking approach based on RFID with sparse reference tags, which can estimate the location of moving objects by detecting and analyzing signal strength distribution of target area. We firstly construct a signal fluctuation ellipse model between RFID reader and tag through the experiments, and then present a localization method based on this model. Then a tracking method based on Hidden Markov Model (HMM) is proposed to predict the trajectory of an object in a passive localization system with sparse reference tag. The experimental results show that our method not only reduces the computation complexity and cost but also ensures the accuracy of localization and tracking.