Design of RLS Wiener FIR filter using covariance information in linear discrete-time stochastic systems

This paper addresses a new design method of recursive least-squares (RLS) finite impulse response (FIR) filter, using the covariance information of the signal and observation noise, and RLS Wiener FIR filter in linear discrete-time stochastic systems. The signal is observed with additive white noise. The signal is assumed to be independent of the white observation noise. The RLS Wiener FIR filter uses the following information: (1) The observation matrix for the signal, (2) the system matrix for the state vector, (3) the variance of the state vector.