Title :
A new approach to spectral estimation: a tunable high-resolution spectral estimator
Author :
Byrnes, Christopher I. ; Georgiou, Tryphon T. ; Lindquist, Anders
Author_Institution :
Dept. of Syst. Sci. & Math., Washington Univ., St. Louis, MO, USA
fDate :
11/1/2000 12:00:00 AM
Abstract :
Traditional maximum entropy spectral estimation determines a power spectrum from covariance estimates. Here, we present a new approach to spectral estimation, which is based on the use of filter banks as a means of obtaining spectral interpolation data. Such data replaces standard covariance estimates. A computational procedure for obtaining suitable pole-zero (ARMA) models from such data is presented. The choice of the zeros (MA-part) of the model is completely arbitrary. By suitable choices of filter bank poles and spectral zeros, the estimator can be tuned to exhibit high resolution in targeted regions of the spectrum
Keywords :
autoregressive moving average processes; filtering theory; interpolation; optimisation; parameter estimation; poles and zeros; signal resolution; spectral analysis; ARMA models; filter bank poles; filter banks; pole-zero models; spectral estimation; spectral interpolation data; spectral zeros; tunable high-resolution spectral estimator; Colored noise; Entropy; Filter bank; Filtering theory; Frequency; Interpolation; Nonlinear filters; Poles and zeros; Signal processing algorithms; Stochastic processes;
Journal_Title :
Signal Processing, IEEE Transactions on