DocumentCode :
1766234
Title :
Self-Contained Pedestrian Tracking During Normal Walking Using an Inertial/Magnetic Sensor Module
Author :
Xiaoli Meng ; Zhi-qiang Zhang ; Jian-Kang Wu ; Wai-Choong Wong ; Haoyong Yu
Author_Institution :
Dept. of Bioeng., Nat. Univ. of Singapore, Singapore, Singapore
Volume :
61
Issue :
3
fYear :
2014
fDate :
41699
Firstpage :
892
Lastpage :
899
Abstract :
This paper proposes a novel self-contained pedestrian tracking method using a foot-mounted inertial and magnetic sensor module, which not only uses the traditional zero velocity updates, but also applies the stride information to further correct the acceleration double integration drifts and thus improves the tracking accuracy. In our method, a velocity control variable is designed in the process model, which is set to the average velocity derived from stride information in the swing (nonzero velocity) phases or zero in the stance (zero-velocity) phases. Stride-based position information is also derived as the pseudomeasurements to further improve the accuracy of the position estimates. An adaptive Kalman filter is then designed to fuse all the sensor information and pseudomeasurements. The proposed pedestrian tracking method has been extensively evaluated using experiments, including both short distance walking with different patterns and long distance walking performed indoors and outdoors, and have been shown to perform effectively for pedestrian tracking.
Keywords :
adaptive Kalman filters; biomedical equipment; biomedical measurement; gait analysis; magnetic sensors; pedestrians; velocity control; acceleration double integration drifts; adaptive Kalman filter; foot-mounted-inertial magnetic sensor module; pedestrian tracking method; process model; pseudomeasurements; self-contained pedestrian tracking method; stride-based position information; swing phases; traditional zero velocity updates; velocity control variable; walking; Acceleration; Adaptation models; Biomedical measurement; Covariance matrices; Foot; Legged locomotion; Magnetometers; Pedestrian navigation; sensor fusion; stride counting; unscented Kalman filter (UKF); zero velocity update;
fLanguage :
English
Journal_Title :
Biomedical Engineering, IEEE Transactions on
Publisher :
ieee
ISSN :
0018-9294
Type :
jour
DOI :
10.1109/TBME.2013.2291910
Filename :
6671426
Link To Document :
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