A Fuzzy Dead Reckoning Algorithm for a Personal Navigator

Shahram Moafipoor, Dorota A. Grejner-Brzezinska, and Charles K. Toth

Abstract:	An example design for a fuzzy Dead Reckoning (DR) algorithm for a personal navigator is proposed here. A DR system for personal navigation can be supported by human dynamics, where Stride Length (SL) and Stride Direction (SD) (heading) are the primary parameters. The sensors which are used to track the operator’s location comprise a range of self-contained sensors including GPS, accelerometer, gyroscope, compass, barometer and step sensors. In our previous research, focused on humandynamic supported navigation during GPS signal blockages, we have shown that these sensors can sense body locomotion in terms of dynamics and geometry representing an implicit function of SL. As an initial implementation of the DR system based on human dynamics, a Radial Basis Function (RBF) artificial neural network was developed, and demonstrated good SL modeling performance in controlled environments. However, in a more realistic environment where the operator’s dynamics changes from walking to running, to climbing stairs, etc., a more complex approach to the DR navigation task must be developed, such as the Knowledge-Based System proposed here, based on fuzzy logic. In principle, once the individual behaviors are defined by fuzzy rules, they can be used to determine and control the model of the state of motion in the current, navigation task. This paper discusses the design and implementation of the fuzzy logic-base Knowledge-Based System, followed by its performance evaluation in the outdoor and indoor environments.
Published in:	Proceedings of the 20th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS 2007) September 25 - 28, 2007 Fort Worth Convention Center Fort Worth, TX
Pages:	48 - 59
Cite this article:	Updated citation: Published in NAVIGATION: Journal of the Institute of Navigation
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