Modified Gaussian Sum Nonlinear Filters for INS/GPS Integrated Systems

M. Nakagawa, H. Okuno, T. Sato, Y. Kubo, S. Sugimoto

Abstract:	In this paper, we present the Gaussian sum quasi-linear opti- mal filter (GQLF), and apply it to land-vehicle INS(Inertial Navigation System)/GPS(Global Positioning System) inte- grated navigation as well as the In-Motion Alignment sys- tems, in comparison with the nonlinear filters such as the Gaussian sum filter (GSF), the quasi-linear optimal filter (QLF) and the Gaussian sum unscented Kalman filters. For many years, the extended Kalman filter has been widely uti- lized as the estimator in the integrated navigation systems, and recently other nonlinear filtering methods are applied. In this paper, we propose a nonlinear filter combining GSF and QLF based on the Markov equivalent linearized technique in order to improve GSF. The combined nonlinear filter is expected that the transient response of the filter can be im- proved under large initial estimation errors. Finally we show the experimental results by using simulated data for various running trajectories, with assuming the various error sources such as the errors of GPS measurement, INS sensors.
Published in:	Proceedings of the 21st International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS 2008) September 16 - 19, 2008 Savannah International Convention Center Savannah, GA
Pages:	2165 - 2176
Cite this article:	Nakagawa, M., Okuno, H., Sato, T., Kubo, Y., Sugimoto, S., "Modified Gaussian Sum Nonlinear Filters for INS/GPS Integrated Systems," Proceedings of the 21st International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS 2008), Savannah, GA, September 2008, pp. 2165-2176.
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