Radio sources identification based on signal parameter analysis

Keywords: recognition algorithm; signal processing; detection;correlation methods; signal modulation.


The article is devoted to the creation of a single portrait of a radio source and methods of its identification. It is known that radio monitoring means are used to detect, identify and locate radio sources. One of the important issues addressed by the radio monitoring system is the reception and identification of the signal. For theidentification purpose the classification questions of the radio sources basic parameters are considered, the modulation types classification and the basic parameters of their types are given. The signal structure allows to determine the autocorrelation and correlation methods. Autocorrelation is used to determine such signal parameters as message duration, data block duration. Correlation allows to identify a specific signal from an existing set. To generate a radio source, two generalized algorithms have been developed: an algorithm for recognizing the type of radio source with unknown parameters and an algorithm for identifying a radiation source according to given parameters. The results of modeling the algorithm for recognizing a radio source with the given parameters are presented. A signature with linear-frequency modulation was used as a given signal. The result of the simulation algorithm is a single extremum with full signal matching; when the signals differ, the extremum width increases, which indicates differences in the signal parameters. An algorithm of this type can be used to search for a given type of signal, which increases the band analysis speed and detection accuracy. It is proved that to increase the detection accuracy it is necessary to use a combination of the above two algorithms with additional digital signal processing, which should increase the accuracy of determining the type of signal and faster finding the parameters of the radio source.


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How to Cite
Pantyeyev, R. (2021). Radio sources identification based on signal parameter analysis. Herald of Kiev Institute of Business and Technology, 46(4), 67-73.