High resolution spectral estimation for noisy signals

Abstract

A spectral model containing poles and zeros is derived for the high resolution spectral estimation of data containing an auto-regressive (all-pole) signal, interference, and white noise. A computationally efficient method for computing the spectrum is introduced. Examples of some spectra calculated by this method are presented and compared with the autoregressive spectral estimator.