Joint AR parameter and order estimation in a general noise environment

A new joint autoregressive (AR) parameter and order estimation approach is presented which works well regardless of noise type. Unlike many other existing AR estimation methods which require prior knowledge of model order and noise statistics, the proposed method provides embedded order estimation in the pole-zero domain without requiring any noise statistics. The joint method virtually achieves the Cramer-Rao bound (CRB) in a general noise environment.