Time-frequency representation for time-varying signals using a Kalman filter

Author

Harashima, Masaharu ; Ferrari, Leonard A. ; Sankar, P.V.

Author_Institution

Dept. of Electr. & Comput. Eng., California Univ., Irvine, CA, USA

Volume

1

fYear

1995

fDate

Oct. 30 1995-Nov. 1 1995

Firstpage

558

Abstract

A new method which uses a Kalman filter to obtain a time-frequency representation for time-varying signals is introduced. In this method, a time-varying signal is modeled as a time-varying AR process whose parameters determine the instantaneous power spectral density (IPSD). Then, a Kalman filter is used to estimate the time-varying parameters which are used to compute the estimated IPSD. From simulation results, it is concluded that a good estimate of the IPSD is obtained with a 2nd order variation model of the time-varying parameters.

Keywords

Kalman filters; autoregressive processes; parameter estimation; signal representation; time-frequency analysis; time-varying filters; Kalman filter; instantaneous power spectral density; second order variation model; time-frequency representation; time-varying AR process; time-varying signals; Amplitude estimation; Chirp; Filters; Frequency estimation; Signal analysis; State estimation; Stochastic resonance; Stochastic systems; Time frequency analysis; Time varying systems;

fLanguage

English

Publisher

ieee

Conference_Titel

Signals, Systems and Computers, 1995. 1995 Conference Record of the Twenty-Ninth Asilomar Conference on

Conference_Location

Pacific Grove, CA, USA

ISSN

1058-6393

Print_ISBN

0-8186-7370-2

Type

conf

DOI

10.1109/ACSSC.1995.540610

Filename

540610