GPS-free terrain-based vehicle tracking on road networks

Prior experiments have confirmed that specific GPS-free terrain-based localization algorithms can perform vehicle tracking in real-time on a single road segment at a time. However, the ability of these algorithms to perform vehicle tracking on large road networks, i.e. across intersections and multiple road segments, has not been verified. In this study, it is shown that it is possible to build upon the existing terrain-based localization algorithms to maintain vehicle tracking in large road networks. A set of estimators based on the Unscented Kalman Filter framework is used to track the vehicle in a section of a road network, i.e. across a few road segments and an intersection. A multiple model estimation scheme, based on comparing incoming attitude measurements with a terrain map, is used to identify the road segment that the vehicle is currently traveling over. Experiments indicate that it is possible to maintain vehicle tracking as a vehicle travels across an intersection in a road network.