基于人工智能的无线电信号调制方式识别  

Recognition of Wireless Radio Signal Modulation Methods based on Artificial Intelligence

作　　者：吴嘉巍 何杰 唐雨淋 WU Jiawei;HE Jie;TANG Yulin(College of Electronic Engineering,Chengdu University of Information Technology,Chengdu 610225,China;Sichuan Tianfu New Area Science and Technology Innovation and Talent Service Bureau,Chengdu 624000,China;Sichuan Provincial Radio Monitoring Station,Chengdu 610000,China)

机构地区：[1]成都信息工程大学电子工程学院,四川成都610255 [2]四川天府新区科技创新和人才服务局,四川成都624000 [3]四川省无线电监测站,四川成都610000

出　　处：《成都信息工程大学学报》2024年第4期430-435,共6页Journal of Chengdu University of Information Technology

摘　　要：近年来越来越多无线电业务和机构的出现,加剧了无线电电磁环境的恶化,因此对无线电信号调制方式的识别是一个重要的研究方向。提出一种基于人工智能的无线电信号调制方式的识别方法,通过利用不同的无线电信号在时频分析图上的特征差异,使用ResNet50深度学习模型完成对无线电信号调制方式的识别分类,在测试集上的识别准确率达95%。通过对比此前基于传统神经网络的无线电调制方式的识别方法,验证了识别结果的准确性和可靠性。实验结果表明,该方法对于无线电信号调制方式的识别具有重要的参考意义。In recent years,the proliferation of wireless radio businesses and organizations has exacerbated the degradation of the electromagnetic environment.Therefore,the identification of modulation methods for wireless radio signals has be-come a crucial research focus.This paper proposes an AI-based method for recognizing modulation methods of wireless radio signals.By leveraging the distinctive features of different wireless radio signals in time-frequency analysis plots,the ResNet50 deep learning model is employed for the classification of modulation methods.The recognition accuracy on the test set reaches 95%.Comparative analysis with traditional neural network methods validate the accuracy and reliability of the proposed approach.Experimental results indicate the significance of this method in the recognition of wireless ra-dio signal modulation methods.

关 键 词：无线电信号 人工智能 调制识别 时频分析 

分 类 号：TP301.6[自动化与计算机技术—计算机系统结构]