论文信息 - Linear estimation from uncertain observations with white plus coloured noises using covariance information

Linear estimation from uncertain observations with white plus coloured noises using covariance information

Abstract This paper considers the least mean-squared error linear estimation problems, using covariance information, in linear discrete-time stochastic systems with uncertain observations for the case of white plus coloured observation noises. The different kinds of estimation problems treated include one-stage prediction, filtering, and fixed-point smoothing. The recursive algorithms are derived by employing the Orthogonal Projection Lemma and assuming that both, the signal and the coloured noise autocovariance functions, are given in a semi-degenerate kernel form.

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