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Proceedings Paper

Multirate sensor fusion for GPS using Kalman filtering, fuzzy methods, and map matching
Author(s): David Mayhew; Pushkin Kachroo
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Paper Abstract

With the advent of the Global Position System (GPS), we now have the ability to determine absolute position anywhere on the globe. Although GPS system work well in open environments with no overhead obstructions, they re subject to large unavoidable errors when the reception from some of the satellites is blocked. This occurs frequently in urban environments, such as downtown New York City. GPS systems require at least four satellites visible to maintain a good position 'fix', and tall buildings and tunnels often block several, if not all, of the satellites. Additionally, due to selective availability, where small amounts of error are intentionally introduced, GPS errors can typically range up to 100 ft or more. This paper proposes several methods for improving the position estimation capabilities of a system by incorporating other sensor and data technologies, including Kalman filtered inertial navigation system, rule- based and fuzzy-based senors fusion techniques, and a unique map-matching algorithm.

Paper Details

Date Published: 8 January 1999
PDF: 10 pages
Proc. SPIE 3525, Mobile Robots XIII and Intelligent Transportation Systems, (8 January 1999); doi: 10.1117/12.335722
Show Author Affiliations
David Mayhew, Virginia Polytechnic Institute and State Univ. (United States)
Pushkin Kachroo, Virginia Polytechnic Institute and State Univ. (United States)

Published in SPIE Proceedings Vol. 3525:
Mobile Robots XIII and Intelligent Transportation Systems
Howie M. Choset; Pushkin Kachroo; Mikhail A. Kourjanski; Douglas W. Gage; Pushkin Kachroo; Marten J. de Vries; Mikhail A. Kourjanski; Marten J. de Vries, Editor(s)

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