Brief paper: New prediction algorithms by covariance information based on innovation theory

Authors:
S. Nakamori;A. Hataji
Affiliations:
Department of Electrical Engineering, Oita University, Oita 870-11, Japan;Department of Electrical Engineering, Oita University, Oita 870-11, Japan
Venue:
Automatica (Journal of IFAC)
Year:
1981

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Abstract

This paper states a new design method of recursive predictor and filter based on the innovations theory, using signal and noise covariance information, for white Gaussian and white Gaussian + coloured observation noises. The derived prediction and filtering algorithms estimate stationary stochastic signal processes. The digital simulation results indicate that the algorithms presented are feasible.