Linear modeling algorithm for tracking time-varying signals

Rafic A. Bachnak

doi:10.1117/12.45640

1 August 1991 Linear modeling algorithm for tracking time-varying signals

Rafic A. Bachnak

Proceedings Volume 1481, Signal and Data Processing of Small Targets 1991; (1991) https://doi.org/10.1117/12.45640
Event: Orlando '91, 1991, Orlando, FL, United States

Abstract

This paper presents a new algorithm for tracking the spectrum of non- stationary signals. In general there is no law relating frequency and time, and therefore, the frequency-time curves are usually approach dependent. The algorithm described here is an extension of the well-known Levinson model for estimating the spectra of stationary signals. The signal parameters are estimated by fitting the model with time-varying coefficients based on an exponential forgetting factor that is introduced to the autocorrelation function. The first operation is the excitation with the input sequence y(n), n equals 0, 1, 2, ..., N, to produce a scalar output, then time-updating by incrementing the previous value with a scalar. To demonstrate the effectiveness of the algorithm, some numerical examples are considered: chirp signal in white noise, two sinusoids, and speech signals.

Citation Download Citation

Rafic A. Bachnak "Linear modeling algorithm for tracking time-varying signals", Proc. SPIE 1481, Signal and Data Processing of Small Targets 1991, (1 August 1991); https://doi.org/10.1117/12.45640

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available