On unbiased parameter estimation of linear systems using noisy measurements

A new least-squares-based method is established to perform unbiased parameter estimation of linear systems using noisy input and output measurements. The significance of the developed method lies in its improved computational efficiency since the underlying noisy system is now identified in a direct manner, with the augmented noisy system being introduced only as an auxiliary system but not actually being identified. Simulation results confirm that the presented efficient implementation scheme can retain the same estimation accuracy with reduced numerical costs.