Consistent parameter estimation of system transfer functions irrespective of noise dynamics

This paper presents a new type of bias-eliminated least-squares (BELS) algorithm to identify transfer function parameters of a linear time-invariant system, irrespective of noise dynamics. Unlike the BELS estimator previously presented in [12], [3], the main feature with the developed algorithm is that the transfer function parameters are consistently estimated in such a direct way that there is no need to prefilter observed data or to deal with a high-order augmented system. This greatly simplifies implementation of the BELS based algorithms and reduces numerical efforts whereas a desirable estimation accuracy can still be achieved. Simulation results are presented which clearly illustrate the good performances of the developed algorithm.