Filtering, smoothing, and prediction using a control-loop spectral factorization method for coloured noise

Abstract

A method for the linear least-squares estimation of random signals contaminated with random noise is shown that uses a new method of spectral factorization. It is shown that the optimal filter can be written entirely in terms of the two spectral factors of signal plus noise and noise-alone, and can be applied to the general case of coloured and white additive noise. The method of spectral factorization used is novel and uses control-system methodology