Centralised Kalman Filter for Augmented GPS Pedestrian Navigation

Vincent Gabaglio

Abstract:	This article presents an algorithm for augmented GPS pedestrian navigation. In this relatively new domain, the combination of GPS with complementary sensors is necessary to provide continuously information about the position. The proposed system contains two accelerometers, one gyroscope and a GPS receiver. The accelerometers bring the information to compute the travelled distance and the gyroscope supply the data to calculate the change of the orientation. The way the sensors raw data are processed and mechanised in the Dead-Reckoning algorithm is explained. An experiment illustrates an effect of the error propagation in the DR algorithm. GPS, when the signals are available, is used firstly to give an absolute position and secondly to adjust the sensors and navigation parameters. This is achieved through a centralised Kalman filter. The kinematic and observation models of the filter are presented. Finally a test and results are presented. With updated about every 2 minutes the proposed combination of sensors is able to keep an accuracy of 15 meters. Suggestions to improve the system are discussed.
Published in:	Proceedings of the 14th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GPS 2001) September 11 - 14, 2001 Salt Palace Convention Center Salt Lake City, UT
Pages:	312 - 318
Cite this article:	Gabaglio, Vincent, "Centralised Kalman Filter for Augmented GPS Pedestrian Navigation," Proceedings of the 14th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GPS 2001), Salt Lake City, UT, September 2001, pp. 312-318.
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