沈阳航空航天大学学报2025，Vol.42Issue(3)：75-81,7.DOI:10.3969/j.issn.2095-1248.2025.03.010
基于循环神经网络的卫星导航系统的欺骗干扰检测算法
Satellite navigation system spoofing interference detection algorithm based on RNN
摘要
Abstract
In order to improve the spoofing interference detection capability of satellite navigation system,a satellite navigation spoofing interference detection algorithm based on RNN was investigated,and the loss function was designed.In order to improve the accuracy of data prediction,a data preprocessing method was studied,which maped the data in a fixed interval and amplifies the characteristics of the data.The experimental results show that the prediction accuracy of the RNN model for the signal-to-noise ratio of ten satellites is higher than that of the Transformer model.The recurrent neural network model has an average accuracy of 64.76%in predicting the signal-to-noise ratio data,while the Transformer model has only 3%.In the RNN prediction model,the accuracy of the prediction for 7 out of 10 satellites signal-to-noise ratios is above 60%.It can be seen that the RNN model has a better prediction effect when facing the signal-to-noise ratio data of BeiDou satellite navigation signals with the time series data type.Therefore,the RNN model can realize the prediction of 0.08dB error for BeiDou signal-to-noise ratio,and when the difference between the future signal-to-noise ratio value and the predicted value is greater than 0.08 dB,it is considered that the signal is a spoofing signal at this time,so as to realize spoofing interference detection.The research results provide certain reference value for the research of satellite navigation spoofing algorithm.关键词
卫星导航系统/深度学习/欺骗干扰检测/信噪比/循环神经网络Key words
satellite navigation system/deep learning/spoofing interference detection/signal-to-noise ratio/recurrent neural network分类
信息技术与安全科学引用本文复制引用
曲萍萍,刘天峰,王尔申,苑子泊,杨健,刘达,石伟,段婉莹..基于循环神经网络的卫星导航系统的欺骗干扰检测算法[J].沈阳航空航天大学学报,2025,42(3):75-81,7.基金项目
国家自然科学基金(项目编号:62173237) （项目编号:62173237）
极限环境光电动态测试技术与仪器全国重点实验室开放基金(项目编号:2023-SYSJJ-04) （项目编号:2023-SYSJJ-04）
中国民航大学民航飞行广域监视与安全控制技术重点实验室开放基金(项目编号:202105) （项目编号:202105）
中国民航飞行技术与飞行安全重点实验室开放基金(项目编号:FZ2021KF15,FZ2021ZZ06). （项目编号:FZ2021KF15,FZ2021ZZ06）
