SPECTRAL-COVARIATION METHOD OF CLASSIFICATION OF RADIO SIGNALS - BORTNYK, Gennadiy; BORTNYK Оlexand; KYRYLYUK, Sergiy (Herald of Khmelnytskyi National University. Technical sciences, 2023)
The paper proposes a high-performance method of radiosignal classification based on spectral-covariance evaluation of signals. At the same time, multi-stage processing of overlapping subsequences of readings of the investigated radiosignal in the time and frequency domain is carried out. At the first stage, it is proposed to evaluate the parameters of the radiosignal based on the found power spectral density of the investigated signal. To determine the spectral density of the radiosignal, subsequences of readings obtained from the array of input readings of the investigated signal are formed. The maximum shift between two adjacent subsequences is chosen, that is, the initial realization of the signal is presented in the form of overlapping subsequences. Taking into account that two adjacent subsequences have part of common processed readings, the paper proposes an expression that for each new subsequence of input readings would take into account the coefficients of the discrete Fourier transform, which were determined for the previous subsequence of the input signal. During the following stages, the shape of the spectrum of the analyzed radiosignal is compared with the spectrum samples specified by the operator of the radiocontrol system. Comparison of the spectrum of the investigated radiosignal and the spectral mask is based on the determined correlation coefficient. The approximation of the value of the correlation coefficient to unity characterizes the degree of linear relationship between the spectrum of the signal and the mask. This makes it possible to determine the type and positions of radiochannels based on the obtained sequence of correlation coefficient values for different shifts of the spectral mask. The analysis of the effectiveness of the proposed method confirmed that thanks to the developed method, it is possible to increase the productivity of the spectral-covariance evaluation of radio signals by 2.0÷8.9 times, depending on the volume of the analyzed implementation of the radiosignal and the number of overlapping subsequences. The maximum performance factor is achieved when the initial implementation of the radiosignal is divided into 64 overlapping subsequences. The proposed method can be used in automated radiotechnical control systems to monitor the radiosituation in real time.