Title :
Unscented Rauch--Tung--Striebel Smoother
Author_Institution :
Helsinki Univ. of Technol., Helsinki
fDate :
4/1/2008 12:00:00 AM
Abstract :
This note considers the application of the unscented transform to optimal smoothing of nonlinear state-space models. In this note, a new Rauch-Tung-Striebel type form of the fixed-interval unscented Kalman smoother is derived. The new smoother differs from the previously proposed two-filter-formulation-based unscented Kalman smoother in the sense that it is not based on running two independent filters forward and backward in time. Instead, a separate backward smoothing pass is used, which recursively computes corrections to the forward filtering result. The smoother equations are derived as approximations to the formal Bayesian optimal smoothing equations. The performance of the new smoother is demonstrated with a simulation.
Keywords :
Bayes methods; Kalman filters; smoothing methods; state-space methods; backward smoothing pass; fixed-interval unscented Kalman smoother; formal Bayesian optimal smoothing equations; forward filtering; independent filters; nonlinear state-space models; unscented Rauch-Tung-Striebel smoother; unscented transform; Bayesian methods; Discrete transforms; Equations; Filtering; Kalman filters; Noise measurement; Smoothing methods; State estimation; Telecommunication computing; Time measurement; Rauch–Tung–Striebel (RTS) smoother; unscented Kalman smoother (UKS); unscented transform;
Journal_Title :
Automatic Control, IEEE Transactions on
DOI :
10.1109/TAC.2008.919531