Estimations of autoregressive signals from noisy measurements

The paper presents an asymptotically unbiased estimator of autoregressive parameters from noisy observations. The key ingredient in the author's method is that a new and simple scheme for estimation of the variance of the white measurement noise is developed. This estimated variance is then used in conjunction with the known technique for elimination of the least-squares estimation bias when the noise statistics are known a priori. The properties of the method are illustrated by means of some simulated examples.