Linear Kalman - Bucy filter with vector autoregressive signal and noise

Abstract

The linear Kalman Bucy filter problem for a system, at that a signal and a noise are vector independent stationary autoregressive processes with orders larger than 1, is investigated. The recurrent equations for filter and its error are delivered. The optimal way of the initial data definition is proposed. Some numerical examples are given. In one of them the algorithm leads to a stationary behavior at infinity. In the other example the Kalman - Bucy filter is impossible because the filter error goes to infinity. A behavior of a signal and its error is illustrated by a simulation of a signal and a noise as vector Gaussian stationary autoregressive processes. The simulation supports theoretical conclusions.