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- W2261509600 abstract "The performance of a linear Kalman filter will degrade when the dynamic noise is not Gaussian. A robust Kalman filter based on the m-interval polynomial approximation (MIPA) method for unknown non-Gaussian noise is proposed. Two situations are considered: (a) the state is Gaussian and the observation noise is non-Gaussian; (b) the state is non-Gaussian and the observation noise is Gaussian. It is shown, as compared with other non-Gaussian filters, the MIPA Kalman filter is computationally feasible, unbiased, more efficient and robust. For the scalar model, Monte Carlo simulations are given to demonstrate the ideas involved." @default.
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- W2261509600 date "1983-05-01" @default.
- W2261509600 modified "2023-09-23" @default.
- W2261509600 title "An adaptive robustizing approach to kalman filtering" @default.
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- W2261509600 doi "https://doi.org/10.1016/0005-1098(83)90104-8" @default.
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