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Nonlinear filtering methods for the INS/GPS in-motion alignment and navigation. (English) Zbl 1196.93088
Proceedings of the 37th ISCIE international symposium on stochastic systems theory and its applications (ISCIE SSS’05), Osaka, Japan, October 28–29, 2005. Kyoto: The Institute of Systems, Control and Information Engineers (ISCIE) (ISBN 4-915740-22-0/pbk). 24-29 (2006).
Summary: We present the algorithms of land-vehicle INS (Inertial Navigation System)/DGPS (Differential Global Positioning System) in-motion alignment based on nonlinear filtering techniques (Quasi-linear optimal filter [Y. Sunahara, An approxiamte method of state estimation for nonlinear dynamical systems, J. Basic Engin., Trans. ASME, Ser. D 92, No. 2, 385–393 (1970)], Gaussian sum filter [D. L. Alspach and H. W. Sorenson, IEEE Trans. Autom. Control 17, 439–448 (1972; Zbl 0264.93023)], Extended Kalman filter [G. Kitagawa, Monte Carlo filter and smoother for non-Gaussian nonlinear state space models, J. Comput. Graph. Stat. 5, 1–25 (1996)] and Monte Carlo filter [A. Doucet, S. J. Godsill and C. Andrieu, On sequential Monte Carlo sampling methods for Bayesian filtering, Statistics and Computing 3, 197–208 (2000)]). We also show results of comparative numerical experiments, and evaluate the nonlinear filtering performance under various error sources such as the errors of GPS, accelerometers and gyros.
For the entire collection see [Zbl 1138.93009].
MSC:
93E11 Filtering in stochastic control theory
93E10 Estimation and detection in stochastic control theory
93C95 Application models in control theory
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