UDC 621.396; 621.391.82
OPTIMIZATION OF STATISTICAL MODELS FOR PIECEWISE-STATIONARY RADIOENGINEERING SIGNALS
V. G. Andrejev, Dr. Sc. (Tech.), full professor, department of Radio engineering systems, RSREU, Ryazan, Russia;
orcid.org/0000-0003-3059-3532, e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.
V. A. Tran, post-graduate student RSREU, Ryazan, Russia; orcid.org/0000-0002-6743-0131, e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.
The optimization of mathematical description for piecewise-stationary radioengineering signals has been carried out. The structure of the algorithm and the proposed method of statistical description are pre-sented. The aim of the work is to increase the computational efficiency of analysis algorithms, and the accuracy of spectral estimation for radioengineering signals on the background of piecewise-stationary noises. The qualitative indicators of the proposed modified spectral analysis method are compared with the conventional autoregression method. Experimental studies have shown that by using the approach proposed for spectral estimation, when compared with known autoregressive methods, it is possible to reduce the discrepancy between control and estimated spectra by 5,2...7,5 times. When conducting a comparative analysis and determining efficiency with a conventional autoregressive model, a decrease in the order of p can be up to 3...5 times. The authors have been confirmed that analyzing the spectrum of radioengineering signals under study relative deviations ΔF of dominant frequency estimate are significantly (up to 6 times) reduced by using the proposed modified method in comparison with autoregressive method. Winnings are achieved through the use of a priori information about time-varying power of interfering process.
Key words: piecewise-stationary noise, weight vector, adaptive algorithm, autoregressive model, moment disorder, spectral estimation, power spectral density.