Adaptive multiple model filter using IMM and STF

Yan Liang, Quan Pan, Dong Hua Zhou, Hong Cai Zhang

科研成果: 期刊稿件文章同行评审

3 引用 (Scopus)

摘要

In fault identification, the Strong Tracking Filter (STF) has strong ability to track the change of some parameters by whitening filtering innovation. In this paper, the authors give out a modified STF by searching the fading factor based on the Least-Squared Estimation. In hybrid estimation, the well-known Interacting Multiple Model (IMM) Technique can model the change of the system modes. So one can design a new adaptive filter - SIMM. In this filter, our modified STF is a parameter-adaptive part and IMM is a mode-adaptive part. The benefit of the new filter is that the number of models can be reduced considerably. The simulations show that SIMM greatly improves accuracy of velocity and acceleration compared with the standard IMM to track the maneuvering target when 2 model-conditional estimators are used in both filters. And the computation burden of SIMM increases only 6% compared with IMM.

源语言英语
页(从-至)167-171
页数5
期刊Chinese Journal of Aeronautics
13
3
出版状态已出版 - 8月 2000

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