ARMA SPECTRAL ESTIMATION OF NARROW-BAND PROCESSES VIA MODEL-REDUCTION

The problem of estimating autoregressive moving average (ARMA) models for narrow-band processes is considered. The following approach is proposed. Estimate a high-order autoregressive (AR) approximation of the process. By model reduction, based on a truncated internally balanced realization or optimal Hankel-norm model reduction, reduce the order of this high-order AR estimate to find a lower order ARMA model. This algorithm gives ARMA spectral estimates with excellent resolution properties, without using iterative numerical minimization methods, as for the maximum likelihood method. How to take the narrow-band assumption into account in the model reduction step is discussed in detail. © 1990 IEEE