全球定位系统2026，Vol.51Issue(2)：91-102,12.DOI:10.12265/j.gnss.2025118
一种基于随机森林模型的GNSS授时欺骗检测方法
A random forest based spoofing detection method for GNSS timing
摘要
Abstract
GNSS has been widely adopted as a primary source of high-precision timing for critical infrastructures such as power grid,communications and financial systems.Its security is therefore essential to the reliable operation of these services.To address the vulnerability of GNSS timing equipment to spoofing attacks,this paper designs a random forest based spoofing detection method for GNSS timing.By leveraging the consistency in signal statistical characteristics arising from the periodic nature of GNSS satellite orbits,the method constructs high discriminative features inspired by kernel function concepts and enhance feature cooperativity through a random forest model,thereby improving detection performance.Tests with real collected data on BeiDou Navigation Satellite System(BDS)B1I and B3I signals show that with 30 decision trees,the model's out-of-bag(OOB)error is approximately 0.13%.The F1-score,which comprehensively balances precision and recall,exceeds 99%on both the independent test set and an additional validation scenario.These results fully validate the method's high accuracy,strong robustness and good generalization capability,confirming its effectiveness in enhancing the security of GNSS timing equipment.关键词
GNSS/欺骗检测/随机森林(RF)/特征工程/授时安全Key words
GNSS/spoofing detection/random forest(RF)/feature engineering/timing security分类
天文与地球科学引用本文复制引用
周非凡,戴旭,肖钰皓,姜蔚,张春玲,何敏,李洪..一种基于随机森林模型的GNSS授时欺骗检测方法[J].全球定位系统,2026,51(2):91-102,12.基金项目
国家电网有限公司科技项目(5700-202441237A-1-1-ZN) （5700-202441237A-1-1-ZN）
