Communication signal classification and recognition method based on multi-feature association and Bayesian network

Abstract

The invention discloses a communication signal classification and recognition method based on multi-feature association and a Bayesian network, and belongs to the technical field of communication signal processing. According to the method, based on characteristics of large fluctuation range of the signal-to-noise ratio and insufficient training samples, features of the time domain, the frequency domain and the space domain of signals are associated, a Bayesian network model is designed, a Bayesian network classifier is obtained through structure learning and parameter learning, and a user cognition result is obtained. According to the method, cognitive classification is performed by employing the Bayesian network classifier, the dependence relations between the features of dimensions can be fully mined, the physical meaning is clear, and the method is applicable to a small-sample condition and an incomplete data set; performing a discretization pre-processing method by employing combination of priori and clustering, and original data information can be reserved to the maximum; and parameter learning is performed on the Bayesian network model by employing random sampling so that good classification accuracy can still be obtained in the conditions of large fluctuation range of the signal-to-noise ratio and insufficient quantity of the training samples.

Description

technical field [0001] The invention belongs to the technical field of communication signal processing, and specifically refers to a communication signal classification and recognition method based on multi-feature association and Bayesian network. Background technique [0002] With the rapid development of electronics and communication technology, radio cognitive technology has been widely used in many fields such as civil frequency domain resource supervision, civil radio communication, and wireless electronic countermeasures. Radio cognition is the process of receiving, identifying and analyzing wireless communication signals. In various radio management fields such as signal confirmation and spectrum monitoring, radio cognition can monitor whether legal radio stations use spectrum resources legally, and at the same time listen to and identify interference signals from illegal stations. In the field of radio communication, radio cognition can enable the receiver to autom...

AI Technical Summary

Problems solved by technology

The goal of the maximum likelihood ratio discriminant recognition method is to maximize the likelihood probability, so the theoretical optimal solution can be obtained, but the expression of this method is usually complicated, and the optimization process is difficult. At the same time, the comparison of model mismatch and parameter deviation sensitive, poor stability

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