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• W2018596299 abstract "This paper discusses the problems related to constructing a receding horizon filter for underwater inertial navigation systems which are subject to external disturbances. Noises are assumed to be bounded, additive, and contained in both state and measurement equations. An estimator is designed according to the sliding-window strategy to minimize the receding horizon estimation cost function. The derived filter is applied to a velocity-aided inertial navigation system. Simulations show that the derived filter is more accurate than the standard Kalman filter (KF) for underwater navigation systems subject to temporary unknown disturbances" @default.
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• W2018596299 date "2006-07-01" @default.
• W2018596299 modified "2023-10-16" @default.
• W2018596299 title "Velocity-Aided Underwater Navigation System Using Receding Horizon Kalman Filter" @default.
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• W2018596299 doi "https://doi.org/10.1109/joe.2006.875100" @default.
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