GNSS Spoofing Detection Using Visual Inertial Odometry

Xiao Zhou, Hong Li, Jian Wen, Yimin Wei, Chun Yang, Mingquan Lu

Peer Reviewed

Abstract: Global navigation satellite system (GNSS) spoofing is becoming an emerging threat to GNSS security for it can induce fake positions at the victim receiver. Recently SLAM (Simultaneous Localization and Mapping) system that is coupled with GNSS has been developed to achieve a better positioning accuracy. However, few existing studies investigated the potential of such scheme to detect GNSS spoofing attacks. This paper proposes a spoofing detection method based on an open-source SLAM system, VINS (Visual-Inertial Navigation System)-Fusion. The proposed method starts with checking the displacement of GNSS measurements and multi-sensor estimation. After the check, the proposed method exploits the transformation matrix of the local frame in VINS-Fusion and the global frame, which is got from the pose-graph optimization. Considering that the transformation matrix is changing slowly generally after every optimization, the sudden change of the matrix may indicate the occurrence of spoofing attacks. We test the performance of VINS-Fusion to verify the necessity to implement spoofing detection in a vision-based state estimation system and explore whether VINS-Fusion can be used to detect spoofing. Moreover, experimental results over public datasets show the effectiveness of our spoofing detection method in certain spoofing scenarios with an acceptable false alarm probability and missed detection probability.
Published in: Proceedings of the 2022 International Technical Meeting of The Institute of Navigation
January 25 - 27, 2022
Hyatt Regency Long Beach
Long Beach, California
Pages: 1392 - 1404
Cite this article: Zhou, Xiao, Li, Hong, Wen, Jian, Wei, Yimin, Yang, Chun, Lu, Mingquan, "GNSS Spoofing Detection Using Visual Inertial Odometry," Proceedings of the 2022 International Technical Meeting of The Institute of Navigation, Long Beach, California, January 2022, pp. 1392-1404.
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