Multirate sensor fusion for GPS using Kalman filtering, fuzzy methods, and map matching

David Mayhew; Pushkin Kachroo

doi:10.1117/12.335722

8 January 1999 Multirate sensor fusion for GPS using Kalman filtering, fuzzy methods, and map matching

David Mayhew, Pushkin Kachroo

Proceedings Volume 3525, Mobile Robots XIII and Intelligent Transportation Systems; (1999) https://doi.org/10.1117/12.335722
Event: Photonics East (ISAM, VVDC, IEMB), 1998, Boston, MA, United States

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.

Citation Download Citation

David Mayhew and Pushkin Kachroo "Multirate sensor fusion for GPS using Kalman filtering, fuzzy methods, and map matching", Proc. SPIE 3525, Mobile Robots XIII and Intelligent Transportation Systems, (8 January 1999); https://doi.org/10.1117/12.335722

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