A Wearable Trajectory Reconstruction System Using Inertial and Magnetic Sensors

This paper presents an inertial-sensor-based wearable device and its associated pedestrian trajectory reconstruction algorithm to reconstruct indoor pedestrian trajectories. The wearable device is composed of a triaxial accelerometer, a triaxial gyroscope, a triaxial magnetometer, a microcontroller, and a Bluetooth wireless transmission module. Users can carry the device to walk in indoor environments at normal speed. A pedestrian trajectory reconstruction algorithm composed of the procedures of data collection, signal preprocessing, and trajectory reconstruction has been developed for reconstructing pedestrian trajectories. In order to minimize the integral errors caused by the intrinsic noise/drift of inertial sensors, we utilize sensor fusion techniques with the Kalman filter for correcting orientation estimation and trajectory reconstruction. The advantages of this wearable device include the following: 1) It can be used anywhere without any external indoor localization technique; and 2) the pedestrian trajectory reconstruction algorithm can reduce integral errors effectively and thus can construct the pedestrian trajectories accurately. Our experimental result on pedestrian trajectory reconstruction has successfully validated the effectiveness of the inertial-sensor-based wearable device and its pedestrian trajectory reconstruction algorithm.