Transfer-function solution of the Kalman-Bucy filtering problem

A novel, transfer-function solution of the Kalman-Bucy time-invariant filtering problem is presented. It is assumed that both message model and noise intensities are time invariant and that the mixture of message and noise has been observed over an infinite interval. This transfer-function approach is based on matrix fractions and spectral factorization of polynomial matrices. It offers an interesting comparison of state-variable and trasnfer-function methods, provides a deep insight into the problem discussed and, what is most important, it is computationally attractive.