RECOGNITION METHOD OF SPECIFIED TYPES OF SIGNAL MODULATION BASED ON A PROBABILISTIC MODEL IN THE FORM OF A MIXTURE OF DISTRIBUTIONS

Abstract

Context. The article considers the features of solving non-traditional problems of recognition of specified types modulation signals in automated radio monitoring. The practical features of this problem determine the increased a priori uncertainty, which consists in the absence of a priori information about the distribution densities of the given signals and the presence of unknown signals. Objective. It is proposed to solve the problem using an unconventional method for the recognition of statistically specified random signals in the presence of a class of unknown signals. This method assumes that for the given signals there is a classified training sample of realizations, according to which the unknown parameters of their distributions are estimated, as well as some threshold values that determine the probabilities of correct recognition of the given types of signal modulation in the presence of unknown signals. Method. A general solution to the problem of recognition of given signals in the presence of unknown signals is given, and recognition methods of types modulation based on the description of signals by probabilistic model in the form of a mixture of distributions are given. The method is based on the description of signals by a probabilistic model in the form of a mixture of distributions and construction of a closed area for given signals in the probabilistic space of signals. Results. Studies of the recognition problems of given types of modulation of signals have been carried out. The studies were performed by statistical tests on samples of signals for radio monitoring of communications. In this case, the decisive rule for recognizing the given types of signal modulation is implemented in software on a computer. As a result of the statistical tests carried out on control samples of signals, estimates of the probabilities of correct recognition of the given types of signal modulation in the presence of unknown signals were obtained. Conclusions. Values of indicators of quality of radio emissions recognition acceptable for the practice of radio monitoring are obtained. The dependences of quality indicators on some conditions and recognition parameters are property. As a result of the research, practical recommendations were obtained on the use of the proposed method for recognizing specified types of signal modulation in automated radio monitoring systems.