Indexed by:Journal Papers

Date of Publication:2019-10-01

Journal:IEEE SENSORS JOURNAL

Included Journals:SCIE、EI

Volume:19

Issue:19,SI

Page Number:8514-8521

ISSN No.:1530-437X

Key Words:Dual-gait analysis; multi-sensor fusion; foot-mounted inertial navigation system (INS); inertial measurement unit (IMU); zero velocity updates (ZUPT)

Abstract:Foot-mounted inertial navigation is an important issue in areas such as pedestrian localization, gait analysis, and sport training. However, low-cost inertial sensors suffer from several errors that make the navigation results less convincing. In this paper, a multi-sensor approach with one sensor on each foot is presented to reduce the system heading drift. Through dual-gait analysis, gait parameters between two feet are employed to make the non-collocated and uncoupled subsystems be related to each other. A step length estimator based on an inverted pendulum model is developed to derive a relative position vector between the two foot-mounted sensors rather than a distance scalar. A Kalman-type filter with one time update and two measurement updates is developed to fuse the velocity and position observations at foot and person levels, respectively. Experiments were conducted by four healthy subjects, and experimental results show that the proposed sensor fusion method can effectively reduce the heading drift of inertial navigation and make the captured dual-foot motion closer to its actual process.