An improved pedestrian inertial navigation system for indoor environments

This paper proposes an improved shoe-mounted inertial navigation system for pedestrian tracking with submeter accuracy. The improvements consist of a fuzzy logic (FL) procedure for foot stance phase detection and an indirect Kalman filter (IKF) for drift correction based on the typical zero-updating (ZUPT) measurement and our proposed angular updating (AUPT) pseudo-measurement. We illustrate our findings using a real time implementation of the proposed approach. Experiments were conducted in an indoor configuration along 300 m trajectory leading to a position accuracy less than 15 cm.