ARMA Spectral Estimation via Model Reduction

Abstract

In this paper we study how to estimate autoregressive moving average (ARMA) processes via a high order autoregressive (AR) estimate and model reduction. The model reduction techniques considered are based on the L2-norm. internally balanced realizations, or the Hankelnorm. We apply this estimation technique to the problem of finding narrow-band signals in white noise.