Signal Quality Monitoring for Discrimination between Spoofing and Environmental Effects, Based on Multidimensional Ratio Metric Tests

Esteban Garbin Manfredini, Beatrice Motella, Fabio Dovis

Peer Reviewed

Abstract:	The security aspects related to the use of Global Navigation Satellite Systems signals have always been, since the beginning of GPS, a reason of concern. Recently, the feasibility of intentional Radio-Frequency Interference attack, such as jamming or spoofing, and their heavy impact on the signal quality have been demonstrated, thus highlighting the vulnerability of a common receiver and further increasing the concern. Many techniques have been proposed in literature for detecting and mitigating the presence of interference signals. One of these techniques, referred to as Signal Quality Monitoring Technique, is a low-complexity signal processing algorithm, based on measurements at the correlators output, able to detect distortions in the correlation peak. The main concern about the use of this kind of technique is the high probability of false alarm induced by environmental effects, such as multipath. The work presented in this paper aims at introducing a new metric that, by considering not only the output of the SQMT, but also other factors, such as the continuity of the effect over time, is able to discriminate between a spoofer attack and environmental effects.
Published in:	Proceedings of the 28th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS+ 2015) September 14 - 18, 2015 Tampa Convention Center Tampa, Florida
Pages:	3100 - 3106
Cite this article:	Manfredini, Esteban Garbin, Motella, Beatrice, Dovis, Fabio, "Signal Quality Monitoring for Discrimination between Spoofing and Environmental Effects, Based on Multidimensional Ratio Metric Tests," Proceedings of the 28th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS+ 2015), Tampa, Florida, September 2015, pp. 3100-3106.
Full Paper:	ION Members/Non-Members: 1 Download Credit Sign In