GNSS Spoofing Detection Using Cumulative Vector Sums

Liam Carey and Mathieu Joerger

Abstract:	This paper describes the development and evaluation of new methods to detect spoofed GNSS signals in Kalman filter-based navigation applications. There are two primary contributions, first, we show that spoofed measurements under a meaconer and a targeted spoofer have a known, specific structure which can be leveraged for detectability. Second, we evaluate three innovations-based monitors, including the cumulative vector sums monitor which is derived from cumulative sum methods that are known to be effective at detecting subtle changes in the mean of a random process. Background is provided on the measurement model derivation, projected innovations method to leverage a known fault structure, innovations monitoring, and the cumulative vector sum monitor. Then, Monte-Carlo analysis is performed to analyze the monitors which shows the improved performance of projected innovations and also provides a case where the CVS monitor outperformed other monitors in probability of detection.
Published in:	Proceedings of the 38th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS+ 2025) September 8 - 12, 2025 Hilton Baltimore Inner Harbor Baltimore, Maryland
Pages:	490 - 502
Cite this article:	Carey, Liam, Joerger, Mathieu, "GNSS Spoofing Detection Using Cumulative Vector Sums," Proceedings of the 38th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS+ 2025), Baltimore, Maryland, September 2025, pp. 490-502. https://doi.org/10.33012/2025.20360
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