Recurrent estimation by an extended observation vector

A recurrent suboptimal algorithm is proposed for filtering a random process whoseunobservable component is described by a linear difference equation while the observable component, as a finite sum of exponential functions of the unobservable component. All coefficients of the equations are random. The proposed algorithm leads to estimates whose accuracy exceeds that of linear ones thanks to the use of polynomial functions of the observable process components.