Electromagnetic signal identification method and device for constructing graph convolutional network based on implicit knowledge

Abstract

The invention discloses an electromagnetic signal identification method and device for constructing a graph convolutional network based on implicit knowledge. The electromagnetic signal identificationmethod comprises the steps: obtaining a plurality of electromagnetic signals, extracting the feature descriptions of the plurality of electromagnetic signals, generating a feature matrix according tothe feature descriptions of the plurality of electromagnetic signals, and enabling the feature matrix to serve as first-class input information; mining implicit knowledge of the plurality of electromagnetic signals, and constructing a graph structure based on the implicit knowledge of the electromagnetic signals as second-class input information according to the implicit knowledge; and building agraph convolutional neural network according to the first type of input information and the second type of input information, and performing loop iteration training on the graph convolutional neuralnetwork by using a weak supervised learning method to enable the graph convolutional neural network to output the types of the plurality of electromagnetic signals. According to the electromagnetic signal identification method, the features of each node can be utilized to mine the relation between the nodes, and the features of each electromagnetic signal category are deeply extracted, and a graphconvolutional neural network is constructed, and the electromagnetic signals are identified, and more information is utilized, and the generalization capability is higher.

Description

technical field [0001] The invention relates to the technical field of electromagnetic signal intelligent perception, in particular to an electromagnetic signal recognition method and device for constructing a graph convolution network based on implicit knowledge. Background technique [0002] Nowadays, with the continuous popularization of mobile communication devices and the vigorous development of Internet of Things technology, especially in the context of the large-scale application of 5G technology and Internet of Things technology, the protection of wireless communication security such as device verification, illegal emission device monitoring, etc., Whether it is in civil communication or industrial manufacturing, it has become more and more important. The extraction of signal subtle features has shown great application value in this field. It can use signal processing technology to identify wireless communication signals and extract subtle features, and then cooperat...

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Problems solved by technology

However, it should be noted that these identification methods relying on artificial design are difficult to guarantee the accuracy

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