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 suitably choices of interbank poles and spectral zeros, the estimator can be tuned to exhibit high resolution in targeted regions of the spectrum.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 3189-3205 |
| Number of pages | 17 |
| Journal | IEEE Transactions on Signal Processing |
| Volume | 48 |
| Issue number | 11 |
| DOIs | |
| State | Published - 2000 |
Bibliographical note
Funding Information:Manuscript received December 28, 1998; revised July 18, 2000. This work was supported in part by grants from AFOSR, NSF, TFR, the Göran Gustafsson Foundation, and Southwestern Bell. The associate editor coordinating the review of this paper and approving it for publication was Dr. Shubha Kadambe. C. I. Byrnes is with the Department of Systems Science and Mathematics, Washington University, St. Louis, MO 63130 USA. T. T. Georgiou is with the Department of Electrical Engineering, University of Minnesota, Minneapolis, MN 55455 USA. A. Lindquist is with the Division of Optimization and Systems Theory, Royal Institute of Technology, Stockholm, Sweden (e-mail: alq@math.kth.se). Publisher Item Identifier S 1053-587X(00)09301-6.
Keywords
- Filter banks
- Interpolation
- Optimization
- Spectral estimation