Localization based on time differences of arrival (TDOA) has turned out to be a promising approach when neither receiver positions nor the positions of signal origins are known a priori. In this paper, we consider calibration-free tracking of a mobile beacon using TDOA, i.e., the positions of the receivers are not given. We propose a probabilistic formulation using a particle filter to simultaneously localize the signal beacon and the receivers. Our method is robust against measurement outliers and incorrect initialization. This is achieved through a probabilistic sensor model for TDOA data which explicitly considers the measurement uncertainty and takes into account disproportional errors caused by measurement outliers. For the reliable initialization of the particle filter, we apply an iterative optimization approach to multiple subsets of TDOA data, where the best solution is implicitly selected by appropriate weighing of the sensor model. We verify the robustness of our approach in extensive experiments in a spacious indoor environment by an ultrasound beacon moving on various trajectories. We demonstrate that our approach ensures a proper initialization of the particle filter and provides accurate position estimates for the signal beacon and the receivers even in case of measurement outliers. Compared to position references of an optical motion capture system we achieve mean position errors below 5 centimeters.
Mendeley saves you time finding and organizing research
Choose a citation style from the tabs below