weighted fusion robust steady-state kalman filters for multisensor system with uncertain noise variances
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2014
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Abstract
A direct approach of designing weighted fusion robust steady-state Kalman filters with uncertain noise variances is presented. Based on the steady-state Kalman filtering theory, using the minimax robust estimation principle and the unbiased linear minimum variance (ULMV) optimal estimation rule, the six robust weighted fusion steady-state Kalman filters are designed based on the worst-case conservative system with the conservative upper bounds of noise variances. The actual filtering error variances of each fuser are guaranteed to have a minimal upper bound for all admissible uncertainties of noise variances. A Lyapunov equation method for robustness analysis is proposed. Their robust accuracy relations are proved. A simulation example verifies their robustness and accuracy relations.
| Reference Key |
qi2014journalweighted
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|---|---|
| Authors | ;Wen-Juan Qi;Peng Zhang;Zi-Li Deng |
| Journal | Chemico-biological interactions |
| Year | 2014 |
| DOI |
10.1155/2014/369252
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| URL | |
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