Nonlinear filtering approaches for INS/GPS integration

Navigation with an integrated INS/GPS approach requires to solve a set of nonlinear equations. In this case, nonlinear filtering techniques such as Particle Filtering methods are expected to perform better than the classical, but suboptimal, Extended Kalman Filter. Besides, the INS/GPS model has a c...

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Bibliographic Details
Published in2004 12th European Signal Processing Conference pp. 873 - 876
Main Authors Giremus, Audrey, Doucet, Arnaud, Escher, Anne-Christine, Tourneret, Jean-Yves
Format Conference Proceeding Journal Article
LanguageEnglish
Published IEEE 01.09.2004
Subjects
Algorithms
Cramer-Rao bounds
Delays
Digital video broadcasting
Equations
Estimates
Filtering
Filtration
Global Positioning System
Navigation
Nonlinearity
Variance
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Summary:Navigation with an integrated INS/GPS approach requires to solve a set of nonlinear equations. In this case, nonlinear filtering techniques such as Particle Filtering methods are expected to perform better than the classical, but suboptimal, Extended Kalman Filter. Besides, the INS/GPS model has a conditionally linear Gaussian structure. A Rao-Blackwellization procedure can then be applied to reduce the variance of the state estimates. This paper studies different algorithms combining Rao-Blackwellization and particle filtering for a specific INS/GPS scenario. Simulation results illustrate the performance of these algorithms. The variance of the estimates is also compared to the corresponding posterior Cramer-Rao bound.
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ISBN:9783200001657
3200001658