A finite-horizon robust Kalman filtering approach for discrete time-varying uncertain systems with additive uncertain-covariance white noises is presented. The system under consideration is subject to uncertainties in both the state and output matrices. The state and gain matrices of the filter are optimized to give a minimal upper bound on the state estimation error covariance for all admissible uncertainties
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Dong et al. (2006) studied this question.
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