Modeling and estimation of asynchronous multirate multisensor system with unreliable measurements


This paper is concerned with state estimation of a linear system by fusion of asynchronous, multirate, multisensor data. The system is described at the best scale with multiple sensors observing a typical factor independently at totally different scales with different sampling rates. Unreliable measurements are obtainable. The main results are: the multiscale system is correctly formulated, a credibility live is made and used to see whether or not the measurement is traditional or faulty, and an optimal recursive fusion algorithm is presented. The effectiveness and stability of the algorithm underneath unreliable measurements are analyzed. A numerical example is given to indicate the feasibility and effectiveness of the presented algorithm.

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