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

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.