Parameter estimation of autoregressive signals from observations corrupted with colored noise

This paper presents a new method for estimation of the parameters of a noisy autoregressive (AR) signal using observations corrupted with colored noise. This method is an improved least-squares (ILS) based method that combines low-order and high-order Yule–Walker equations. The performance of the proposed method is illustrated using computer simulations.