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

Volume

48

Issue

11

fYear

2000

fDate

11/1/2000 12:00:00 AM

Firstpage

3189

Lastpage

3205

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;

fLanguage

English

Journal_Title

Signal Processing, IEEE Transactions on

Publisher

ieee

ISSN

1053-587X

Type

jour

DOI

10.1109/78.875475

Filename

875475