Spectrum estimation by iterative minimization of the I-divergence measure

Author

White, Langford B.

Author_Institution

Defence Sci. & Technol. Organ., Salisbury, SA, Australia

Volume

40

Issue

11

fYear

1992

fDate

11/1/1992 12:00:00 AM

Firstpage

2863

Lastpage

2866

Abstract

A method for spectrum estimation (either narrowband or broadband) based on minimization of Csiszar´s (1975) I-divergence measure is introduced. The blurring effect of the observation window (or antenna array) is minimized by applying a nonlinear deconvolution procedure. This algorithm has subsequently been shown to minimize the I-divergence between the spectrum and its estimate subject to a non-negativity constraint. Here the method is applied to the spectrum estimation problem for stationary processes. A reblurring procedure is used to regularize the method. Simulations show that the method offers error performance comparable to that of MUSIC, although the resolution performance is inferior. The method is iterative, allowing a tradeoff between resolution and error performance, and can be implemented using fast FFT hardware

Keywords

inverse problems; iterative methods; minimisation; parameter estimation; spectral analysis; FFT hardware; I-divergence measure; blurring effect; deterministic inverse problem; iterative minimization; nonlinear deconvolution procedure; nonnegativity constraint; observation window; reblurring procedure; resolution performance; spectrum estimation; stationary processes; Antenna arrays; Antenna measurements; Deconvolution; Hardware; Iterative algorithms; Iterative methods; Minimization methods; Multiple signal classification; Narrowband; Spectral analysis;

fLanguage

English

Journal_Title

Signal Processing, IEEE Transactions on

Publisher

ieee

ISSN

1053-587X

Type

jour

DOI

10.1109/78.165681

Filename

165681