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A Classification Method of Illegal Broadcasting Signals Based on Recurrent Neural Network

A technology of cyclic neural network and illegal broadcasting, which is applied in the field of radio signal monitoring and management, can solve problems such as the inability to effectively realize the identification of illegal broadcasting signals of radio signals, and achieve the effects of easy supervision and investigation, high recognition accuracy and simple operation

Active Publication Date: 2021-03-26
DALIAN UNIV OF TECH +1
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Problems solved by technology

Therefore, most of these schemes cannot effectively realize the supervision of radio signals and the identification of illegal broadcast signals

Method used

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  • A Classification Method of Illegal Broadcasting Signals Based on Recurrent Neural Network
  • A Classification Method of Illegal Broadcasting Signals Based on Recurrent Neural Network
  • A Classification Method of Illegal Broadcasting Signals Based on Recurrent Neural Network

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Embodiment Construction

[0033] The specific implementation manners of the present invention will be further described below in conjunction with the accompanying drawings and technical solutions.

[0034] The classification method of illegal broadcasting signals based on cyclic neural network, the overall block diagram of the system is as follows figure 1 shown. The method can be divided into four links, namely: signal data collection, signal data quality judgment, frequency point library + neural network classification, and prediction value processing. Among them, the signal data acquisition process can obtain the data required for the experiment, and save the frequency point information in the data to classify the frequency point library. The function of signal data quality judgment is to judge the quality of data, and the quality of data directly affects the accuracy of classification. The pre-classification of the frequency point library can distinguish the illegal broadcast signal of the illega...

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Abstract

The invention discloses a method for classifying illegal broadcast signals based on a cyclic neural network, and belongs to the technical field of radio signal monitoring and management. First, use LabVIEW and USRP to receive broadcasting station signals, and after the quality judgment of the received signals, the data of each frequency point is segmented to produce training samples and test samples. Using the legal broadcast signal frequency library to compare the pre-classification to distinguish illegal signals with illegal frequency points, and then use deep learning to classify the predicted value of the network output signal, and then perform data processing on the predicted value to complete the classification and identification of illegal broadcast signals. The present invention can judge whether there is an illegal signal with fast speed and high precision, has simple operation, and is helpful for the radio management department to monitor and manage the radio stations.

Description

technical field [0001] The invention belongs to the technical field of radio signal monitoring and management, and relates to a method for classifying illegal broadcast signals based on a cyclic neural network, which is a method for classifying and identifying illegal broadcast signals by using a cyclic neural network. Background technique [0002] Illegal broadcast signals are illegal radio stations that are set up without the approval of the radio and television management department and the radio management agency and use broadcast frequencies to broadcast to the public. If it is not controlled, it will disrupt the broadcast order, interfere with civil aviation communications, and even affect social stability. Therefore, an effective way to monitor illegal broadcast signals is needed. After investigation, it is found that there are few studies on direct monitoring of illegal broadcast signals, and there are mainly two methods for radio fingerprint identification associate...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06K9/62
CPCG06F18/2431G06F18/214
Inventor 邱天爽刘浩李蓉李景春
Owner DALIAN UNIV OF TECH