An Identification Method for Single-Input Single-Output Linear Systems with Colored Output Noise Using Eigenvector Method

Abstract

A new algorithm is proposed to estimate parameters of Single-Input Single-Output system with colored output noise using eigenvector method. The algorithm is an expansion of the previously proposed algorithms proposed by the author with iterative estimation of the variances of noises. The newly proposed algorithm uses an iterative calculation and it consists of two parts. One part is the estimation of the system parameters using the variances and autocovariances of output noises. And it is assumed that the input noises are white Gausian noise with very small variances. The estimation of the system parameters is one of the least squares identification algorithms using eigenvector. The other part is the estimation of the variance and autocovariace of output noises using the estimated system parameters. Some simulations show the effectiveness of the proposed method.