An efficient subband decomposition based on the Hilbert transform for high-resolution spectral estimation

Author

Rouquette, S. ; Berthoumieu, Y. ; Najim, M.

Author_Institution

ENSERB, CNRS, Talence, France

fYear

1996

fDate

18-21 Jun 1996

Firstpage

409

Lastpage

412

Abstract

This paper deals with high-resolution frequency estimation for narrow-band plane waves. We propose an approach based on subband decomposition in the spectral domain to improve the performance of high-resolution analysis. This decomposition is based on the Hilbert transform for one and two-dimensional signals. This improvement is tested on ESPRIT and MEMP techniques. We first present the subband decomposition based on the Hilbert transform (SDBHT) for one-dimensional (1D) signals. Secondly the SDBHT method is extended to the two-dimensional (2D) case. Finally the advantages of such a method are illustrated with simulation examples

Keywords

Hilbert transforms; frequency estimation; signal resolution; spectral analysis; spectral-domain analysis; ESPRIT; Hilbert transform; MEMP techniques; SDBHT method; efficient subband decomposition; high-resolution spectral estimation; narrow-band plane waves; one-dimensional signals; spectral domain; two-dimensional signals; Chirp modulation; Filtering; Frequency estimation; Frequency modulation; Hydrogen; Low pass filters; Mirrors; Nonlinear filters; Signal processing; Signal to noise ratio;

fLanguage

English

Publisher

ieee

Conference_Titel

Time-Frequency and Time-Scale Analysis, 1996., Proceedings of the IEEE-SP International Symposium on

Conference_Location

Paris

Print_ISBN

0-7803-3512-0

Type

conf

DOI

10.1109/TFSA.1996.550079

Filename

550079