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arXiv 2404.02432eess.SP

基于众包双差伪距空间分布的 GNSS 欺骗检测

GNSS Spoofing Detection by Crowdsourcing Double Differential Pseudorange Spatial Distribution

Xin Chen, Kai Wang

AI总结:

提出一种基于众包双差伪距空间随机集方差的三层假设 GNSS 欺骗检测方法,可识别无欺骗、完全和部分欺骗,且复杂度低、抗多径、适应性强。

摘要:

众所周知,欺骗是一种严重威胁,会对 GNSS 应用的可靠性和准确性造成不利影响。本研究构建了众包双差伪距空间(D2SP)随机集,并推导了该集合的分布。基于 D2SP 集合的方差,设计了一种三层假设检测算法,用于对感兴趣区域(ROI)内的无欺骗、完全欺骗和部分欺骗情形进行分类。该算法不需要接收机真实位置或相对距离的先验知识。仿真测试结果表明,与广义似然比检验(GLRT)方法相比,所提出的 D2SP 欺骗检测方法具有计算复杂度更低、对多径误差容忍度更高的优势;GLRT 是当前基于多接收机差分伪距的主流欺骗检测算法。此外,该方法对不同大小的 ROI 和不同数量的众包接收机也表现出更好的灵活性。

英文摘要:

It is widely known that spoofing is a major threat that adversely impacts the reliability and accuracy of GNSS applications. In this study, a crowdsourcing double differential pseudorange spatial (D2SP) random set is constructed and the distribution of the set is derived.Based on the variance of the D2SP set, a tri-level hypothesis detection algorithm is designed to classify spoofing-free, fully-spoofed, and partially-spoofed cases in the region of interest (ROI).It does not require the prior knowledge of the truth positions or relative distances of the receivers.Simulation test results show that the proposed D2SP spoofing detection method has the advantages of lower computational complexity and higher tolerance for multipath errors compared with the generalized likelihood ratio test (GLRT) method that is the current mainstream spoofing detection algorithm based on multiple receivers' differential pseudoranges.Moreover, it also shows better flexibility for different sizes of ROI and numbers of the crowdsourcing receivers.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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