Abstract
It is well known that least-squares (LS) method gives biased parameter estimates when the input and output measurements are corrupted by white noise. One possible approach for solving this bias problem is the bias-compnesation based method such as the bias-compensated least-squares (BCLS) method. In this paper, a new bias-compensation based method is proposed for identification of noisy input-output system. The proposed method is based on compensation of asymptotic bias on the instrumental variables type (IV-type) estimates by making use of noise variances estimates. In order to obtain the noise variances estimates, an overdetermined system of equations is introduced, and the noise variances estimation algorithm is derived by solving this overdetermined system of equations. From the combination of the parameter estimation algorithm and the noise variances estimation algorithm, the proposed bias-compensated instrumental variables type (BCIV-type) method can be established. The resuluts of a simulated exmple indicate that the proposed algorithm provides good estimates.
