Pedestrian Navigation Method based on PDR/INS KF fusion and Height Update for Three-Dimensional Positioning

Abstract

Inertial navigation system (INS) and pedestrian dead reckoning (PDR) that use wearable MEMS inertial measurement units (IMUs) can track the location of a pedestrian on two-dimensional (2D) plane. This paper proposes a pedestrian navigation method based on INS/PDR Kalman filter (KF) fusion to calculate the trajectory of a pedestrian in indoor corridors, which can effectively suppress the heading drift. Besides, the height update algorithm is introduced based on the pressure output of a barometer to constrain the height divergence for three-dimensional (3D) positioning. The results of motion experiment show that the navigation accuracy of INS/PDR Kalman filter fusion method is significantly increased compared with the INS. The proposed height update algorithm have better correction effect on the problem of height divergence compared with ZUPT-aided inertial navigation algorithm.