Established in 2005 under support of MŠMT ČR (project 1M0572)

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Adaptive choice of scaling parameter in derivative-free local filters

Typ:
Conference paper
Proceedings name:
Proceedings of the 13th International Conference on Information Fusion
Serie:
Edinburgh, UK
Year:
2010
ISBN:
978-0-9824438-1-1
Keywords:
state estimation, nonlinear filtering, Kalman filtering
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Anotation:
The paper deals with adaptive choice of the saling parameter in derivative-free local filters. In the last decade several novel local derivative-free filtering methods have been proposed. These methods exploiting Stirling’s interpolation and the unscented transformation are, however, conditioned by specification of a scaling parameter significantly influencing the quality of the state estimate. Surprisingly, almost no attention has been devoted to a suitable choice of the parameter. In fact, only a few basic recommendations have been provided, which are rather general and do not respect the particular system description. The choice of the parameter thus remains mainly on a user. The goal of the paper is to provide a technique for adaptive choice of the scaling parameter of the derivative-free local filters.
 
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