Title :
Unscented Kalman Filter: Aspects and Adaptive Setting of Scaling Parameter
Author :
Jindřich Dunik;Miroslav Simandl;Ondřej Straka
Author_Institution :
Department of Cybernetics, Faculty of Applied Sciences, University of West Bohemia, Pilsen, Czech Republic
Abstract :
This technical note deals with the unscented Kalman filter for state estimation of nonlinear stochastic dynamic systems with a special focus on the scaling parameter of the filter. Its standard choice is analyzed and its impact on the estimation quality is discussed. On the basis of the analysis, a novel method for adaptive setting of the parameter in the unscented Kalman filter is proposed. The results are illustrated in a numerical example.
Keywords :
"Covariance matrix","Kalman filters","Approximation error","Algorithm design and analysis","State estimation","Prediction algorithms"
Journal_Title :
IEEE Transactions on Automatic Control
DOI :
10.1109/TAC.2012.2188424