A Foot-Mounted Sensor Based 3D Indoor Positioning Approach

Abstract

We present a 3D indoor positioning system with foot mounted low cost MEMS sensors. The sensors includes the accelerometers, gyroscopes, and barometer. The output of accelerometers and gyroscopes are used to calculate the zero velocity update (ZUPT) and the movement of one step. The barometer is used to detect the altitude changes. A Kalman filter based framework is used to fusion the outputs of the sensors and estimate the non-linear errors of the position and heading, which increased over time. A particle filter is used to further reduce the errors. The test result shows that the designed system perform well.