High-Resolution ARMA Estimation of Mixed Spectra

In this paper, we propose a high-resolution autoregressive moving average (ARMA) modeling technique for signals which are a sum of sinusoids embedded in colored noise. The approach is based on a special ARMA model. We show that an approximation to this model can be found through the central solution of Nevanlinna-Pick interpolation. In this context, it can reach a very fine resolution with a special arrangement of filterbank poles. A very efficient iterative algorithm will then be presented to achieve such desired arrangement. We also derive theoretical expressions for the variance of interpolation values for both continuous and mixed spectra for complex poles. Computer simulations show that the approach is very powerful in joint power spectrum and frequency estimation and provides superior performance with respect to traditional techniques.