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Proceedings Paper

Linear modeling algorithm for tracking time-varying signals
Author(s): Rafic A. Bachnak
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Paper 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.

Paper Details

Date Published: 1 August 1991
PDF: 11 pages
Proc. SPIE 1481, Signal and Data Processing of Small Targets 1991, (1 August 1991); doi: 10.1117/12.45640
Show Author Affiliations
Rafic A. Bachnak, Franklin Univ. (United States)


Published in SPIE Proceedings Vol. 1481:
Signal and Data Processing of Small Targets 1991
Oliver E. Drummond, Editor(s)

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