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基于SCS的多星联合诱导式欺骗检测算法 被引量:1

SCS⁃based multi⁃star joint induced spoofing detection algorithm
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摘要 欺骗式干扰严重威胁卫星导航接收机的信息安全,其中诱导式欺骗干扰可以在不令目标接收机失锁的状态下,隐蔽地夺取跟踪环路的控制权,加大了检测欺骗的难度。此外,多径干扰可能会造成基于信号质量监测(SQM)的欺骗检测算法虚警。文中提出一种基于S曲线过零点斜率(SCS)的多星联合欺骗检测算法,通过检验接收机遭受欺骗攻击时不同方向卫星的一致性,区分多径干扰与欺骗攻击。分别使用美国德州大学实采欺骗信号数据集(TEXBAT)与卫星信号模拟器生成的含有多径干扰的卫星信号进行实验分析。实验结果表明,所提出算法检测诱导式欺骗攻击时响应迅速,欺骗检测性能相较于三种传统的SQM算法更优,同时对于多径干扰有较强的鲁棒性。 Spoofing interference is a serious threat to the information security of satellite navigation receiver.Induced spoofing interference can seize the control of the tracking loop without unlocking the target receiver,which increases the difficulty of spoofing detection.In addition,when the receiver is in the multipath environment,the multipath interference signal may cause false alarms of the SQM(signal quality monitoring)based spoofing detection algorithms.In order to effectively solve the above problems,a multi⁃star joint spoofing detection algorithm based on SCS(S curve slope)is proposed,which can distinguish multipath interference from spoofing attacks by checking the consistency of satellites in different directions when the receiver is under spoofing attacks.The Texas Spoofing Test Battery(TEXBAT)generated by University of Texas and the satellite signals containing multipath interference generated by the signal simulator were respectively utilized to evaluate the proposed algorithm.The experimental results show that,in comparison with three traditional SQM algorithms,the proposed algorithm has higher response speed,better spoof⁃detection performance and stronger robustness for multipath interference.
作者 朱瑞晨 王文益 ZHU Ruichen;WANG Wenyi(Tianjin Key Laboratory for Intelligent Signal and Image Processing,Civil Aviation University of China,Tianjin 300300,China)
出处 《现代电子技术》 2023年第11期1-8,共8页 Modern Electronics Technique
基金 国家自然科学基金项目(U2133204) 中国民航大学研究生科研创新项目(2021YJS023)。
关键词 卫星导航 诱导式欺骗 SCS 欺骗检测 多星联合检测 多径干扰 信号质量监测 satellite navigation induced spoofing SCS spoofing detection multi⁃star combined detection multipath interference signal quality monitoring
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