Errors-in-variables identification through covariance matching: Analysis of a colored measurement noise case

The method of covariance and cross-covariance matching is considered for errors-in-variables identification where the measurement noises are colored. The covariance and cross-covariance functions are estimated from the noise- corrupted data and the corresponding theoretical functions, parameterized by the unknown parameters, are matched to the estimated functions. The main contribution of the paper is a step-by-step algorithm for the computation of the covariance matrix of the estimated system parameters.