LAUSR

This paper proposes an inertial sensor-based positioning method without using dead reckoning. The basic concept estimates the current position based on a pre-indexed map composed of spectrograms of road shapes estimated using inertial sensor signals. The proposed positioning algorithm has three characteristics: a feature-indexed map, the Kalman filter for signal fusion, and the interacting multiple model to integrate multiple maps. The positioning algorithm shows higher positioning accuracy and shorter computing time than a simple scanning method. Furthermore, the size of the map does not proportionally increase as the total length of the road increases. Therefore, the proposed positioning algorithm can be used as a complementary or alternative positioning method to GPS-based positioning methods using only an inertial sensor that is cheap and reliable.