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Journal Radioengineering №11 for 2016 г.
Article in number:
Parametric spectral analysis of signals with a gaussian shape of the spectrum under the influence of additive noise
Keywords: spectrum spectral estimation discrete autocorrelation function autocorrelation sequence autoregression model autore-gression power spectral density parametric evaluation
Authors:
V.G. Andreev - Dr. Sc. (Eng.), Associate Professor, Professor, Department of Radio Systems, Ryazan State Radio Engineering University E-mail: andrejev.v.g@rsreu.ru N.L. Tran - Post-graduate Student, Ryazan State Radio Engineering University E-mail: ngoclucryazan@gmail.com
Abstract:
We proposed and investigated a method of restoring the autocorrelation coefficients for unimodal random signal spectrum to build their autoregression models. The method is based on solving a system of equations which is used between the measured dependence of the autocorrelation coefficients when exposed to additive white Gaussian noise. Experimental have shown that the proposed approach makes it possible to reduce the - times the discrepancy between the control and the model spectrum as compared to the known methods of spectral analysis, in particular AR-method.
Pages: 68-73
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