Map-based Autonomous Personal Localization and Tracking

An autonomous localisation and tracking method is a method independent from the reception of external data. In our approach we ignore methods like GPS- and WiFi- positioning and we focus on the use of inertial navigation system (INS) carried by the person and connected to a map database. The walking person is considered as a dynamic system, whose movements are measured by the INS. His trajectory is modified with respect to a dedicated motion model. Users location is estimated in the frame of Bayesian inference and is based on the association of the trajectory to the map database, a technique known as map- matching. Because of the non-linear nature of the estimation problem, non-inear filtering techniques like particle filters (Sequential Monte Carlo methods) are applied. In tracking mode simple geometric constrains will be observed in order to associate every point of the trajectory to element of the map database. In parallel the localisation mode rest active in order to keep the knowledge on the history of measurements. The algorithm is tested on the campus of EPFL; the process of localisation is entirely autonomous and gives promising results. That method of localisation can be applied to many pedestrian navigation tasks, in particular for the needs of the fire-brigades and security services.