On foot navigation: continuous step calibration using both complementary recursive prediction and adaptive Kalman filtering

Quentin Ladetto

Abstract:	Dead reckoning for on-foot navigation applications cannot be computed by double integration of the antero- posterior acceleration. The main reasons are the alignment problem and the important sensor systematic errors in comparison to human walking speed. However, raw accelerometer signal can furnish helpful information on steps length as a function of the walk dynamics. As stride length naturally varies, a continuous adaptation is necessary. In the absence of satellite observable, a recursive prediction process is used. When GPS signal is available, adaptive Kalman filtering is processed to update both the stride length and the recursive prediction parameters. This paper shows the different necessary stages for individual stride calibration as basis of global on-foot dead reckoning applications. This study lies within the framework of a project that aims at analyzing the daily activity of people. Precise continuous positioning, but not necessarily in real-time conditions, appears of evident interest. The global procedure and several test results are presented.
Published in:	Proceedings of the 13th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GPS 2000) September 19 - 22, 2000 Salt Palace Convention Center Salt Lake City, UT
Pages:	1735 - 1740
Cite this article:	Ladetto, Quentin, "On foot navigation: continuous step calibration using both complementary recursive prediction and adaptive Kalman filtering," Proceedings of the 13th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GPS 2000), Salt Lake City, UT, September 2000, pp. 1735-1740.
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