Cooperative Hybrid Localization Using Gaussian Processes And Belief Propagation

Wireless localization using signal strength has been very popular in commercial applications due to the wide availability of 802.11 WiFi networks. However, signal strength information alone provides very rough location estimates. In this paper we consider supplementing the receiver of each user with a ranging unit required for accurate positioning. By allowing range-based cooperation between the users, it becomes possible to increase the positioning accuracy without the need of a fully deployed network of ranging anchors. To this end, we propose a fully distributed localization algorithm that uses belief propagation for fusing signal strength and ranging information. Extensive simulations, using 3D ray tracing to provide accurate radio maps, show that the proposed fusion of measurements results in a very scalable localization solution, where the localization performance smoothly transitions in accuracy, depending on the available infrastructure.