Introduction

The modelling concerns either the system generating the observation whose PSD we want to estimate: parametric methods, or the signal itself: maximum likelihood method [15].

Parametric spectral estimation methods use a model to obtain an estimate of the spectrum. Based on a priori knowledge of the process, these models fall into three main categories:

  • Autoregressive (AR) models

  • Adjusted mean (MA) models

  • autoregressive average-adjusted (ARMA) models.

We break down the parametric approach into three steps:

  1. Choose a model that describes the process appropriately.

  2. Estimate model parameters based on available data.

  3. Estimate the spectrum based on the model parameters.