An Adaptive Iterated Kalman Filter

descriptionPublicationkeyboard_double_arrow_right Article 01 Oct 2006Publisher:IEEEJournal:The Proceedings of the Multiconference on "Computational Engineering in Systems Applications"

Authors: Yong-An Zhang; null Di Zhou; Guang-ren Duan;

doi: 10.1109/cesa.2006.313591 , 10.1109/cesa.2006.4281916

An Adaptive Iterated Kalman Filter

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Abstract

The recursive filtering of discrete-time nonlinear systems in the presence of unknown noise statistical parameters is studied. By embedding the modified Sage-Husa noise statistics estimator into the iterated Kalman filter, an adaptive iterated Kalman filter is obtained. With iterative operations as well as the online estimation of unknown covariance of virtual noise, linearized error can be reduced. As a result, the estimation performance is improved. A numerical example shows the effectiveness of the proposed filter.

Related Organizations

Harbin Institute of Technology
China (People's Republic of)

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