Centralized cooperative positioning and tracking with realistic communications constraints

In this paper, we investigate the performance of centralized cooperative positioning algorithms. Compared to traditional positioning algorithms which solely exploit ranging information from anchor nodes, cooperative positioning additionally uses measurements from peer-to-peer links between the users. Since we are proposing a centralized architecture, all information has to be collected at a central entity for position calculation and further provision to the network. Hence, besides position-relevant metrics like accuracy and coverage also communications overhead and latency and their impact on the overall performance will be assessed. As we are considering a dynamic scenario, the cooperative positioning algorithms are based on extended Kalman filtering for position estimation and tracking. Simulation results for ultra-wideband based ranging information and WLAN based communications infrastructure show the benefits of cooperative position and tracking for realistic measurement and mobility models.