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

A Bayesian network and communication signal technology, applied in the field of communication signal classification and recognition based on multi-feature correlation and Bayesian network, can solve the problems of difficult optimization process, complex expression, model mismatch and parameter deviation sensitivity, etc. Achieve the effect of improving classification accuracy, clear physical meaning, and good classification accuracy

Active Publication Date: 2019-03-08
BEIHANG UNIV
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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 expressi

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

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[0024] The specific implementation method of the present invention will be further described in detail below in conjunction with the accompanying drawings.

[0025] The present invention provides a communication signal classification and recognition method based on multi-feature association and Bayesian network, such as figure 1 Shown is a structural block diagram of a communication signal classification and identification system for implementing the communication signal classification and identification method, the system includes an input module, a Bayesian network classifier and an output module, and the input module input includes The communication signal sample data set constructed by feature correlation in the spatial domain, frequency domain, and time domain is used to train the Bayesian network classifier; the Bayesian network classifier is the result of Bayesian network model learning, including Bayesian The structure and parameters of the network model are two parts;...

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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...

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Application Information

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IPC IPC(8): H04L27/00G06K9/62G06K9/00
CPCH04L27/0012G06F2218/12G06F18/24155
Inventor 丁文锐刘西洋刘春辉张多纳
Owner BEIHANG UNIV
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