Multiresolutional filtering of a class of dynamic multiscale system subject to colored state equation noise

Authors:
Peiling Cui;Quan Pan;Guizeng Wang;Jianfeng Cui
Affiliations:
Department of Automation, Tsinghua University, Beijing, China;Department of Automatic Control, Northwestern Polytechnical University, Xi’an, Shaanxi, China;Department of Automation, Tsinghua University, Beijing, China;Department of Automatic Control, Northwestern Polytechnical University, Xi’an, Shaanxi, China
Venue:
DCOSS'05 Proceedings of the First IEEE international conference on Distributed Computing in Sensor Systems
Year:
2005

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IEEE Transactions on Information Theory

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Abstract

In this paper, modeling and estimation of a class of dynamic multiscale system subject to colored state equation noise is proposed. The colored state noise vector is augmented in the system state variables, the state space projection equation is used to link the scales, and then a new system model is built. The new model is in a form suitable for the application of the Kalman filter equations. Haar-wavelet-based model and estimation algorithm are given. Monte Carlo simulation results demonstrate that the proposed algorithm is effective and powerful in this kind of multiscale estimation problem.