强激光与粒子束2024，Vol.36Issue(4)：137-144,8.DOI:10.11884/HPLPB202436.230380
基于重要区域定位与掩码的射频指纹可视化分析
Visual analysis method for RF fingerprint based on important region localization and masking
摘要
Abstract
A Grad-CAM based visualizing method for important regions is proposed for the interpretability of RF fingerprint extraction and deep learning models of time-domain pulse signal samples.The impact of important regions on RF fingerprint recognition results is analyzed through multiple mask tests of important regions.Based on signal samples of 10 emitters,the test results of two ResNet models with different layers are compared.It is found that the proposed method can distinguish different types of signals and present individual differences.Analysis shows that this method can detect important regional localization differences when different emitters send the same signal,and can visually reflect the spatial distance of RF fingerprint characteristics,as well as the differences in feature representation and fingerprint localization accuracy of different models;At the same time,it is found that masks for important areas are more prone to false predictions,which proves the existence of RF fingerprints related to time-frequency characteristics in specific signals,and can assist in visualizing key points that affect the recognition of RF fingerprint samples.关键词
可解释性/射频指纹/深度学习/可视化/信号特征Key words
interpretability/radio frequency fingerprint/deep learning/visualization/signal characteristics分类
信息技术与安全科学引用本文复制引用
刘文斌,范平志,杨佳煌,李雨锴,王钰浩,孟华..基于重要区域定位与掩码的射频指纹可视化分析[J].强激光与粒子束,2024,36(4):137-144,8.基金项目
西南交通大学交叉培育项目(2682023TPY027) （2682023TPY027）
