This paper will present an exercise to verify the usefulness of statistical testing of measurement residuals of an overdetermined position solution followed by measurement subset selection for spoofing detection and mitigation for certain spoofing events, to be especially beneficial when multi-GNSS is considered. Tests include utilizing dynamic GPS spoofing data from the TEXBAT testing battery. We will present that Advanced RAIM (Receiver Autonomous Integrity Monitoring) has benefits for spoof detection. RAIM is designed to catch inconsistencies in range measurements and is thus useful in defeating a surreptitious lift off spoofing attack. Inconsistencies in a lift off attack exist when the spoof signal mixes with the genuine signal of similar power levels (within a few dB). The mixing creates some measurements from genuine signals and some from the spoofed signals. ARAIM cannot however mitigate across all categories of spoofers and hence should not represent a standalone spoofing solution. Although pre-and post-correlation signal processing is definitely the most efficient way to detect and mitigate spoofing effects, checking the measurements in the navigation domain is not a lost cause, as presented herein.

Feasibility of fault exclusion related to advanced RAIM for GNSS spoofing detection

Innac,A.
2017

Abstract

This paper will present an exercise to verify the usefulness of statistical testing of measurement residuals of an overdetermined position solution followed by measurement subset selection for spoofing detection and mitigation for certain spoofing events, to be especially beneficial when multi-GNSS is considered. Tests include utilizing dynamic GPS spoofing data from the TEXBAT testing battery. We will present that Advanced RAIM (Receiver Autonomous Integrity Monitoring) has benefits for spoof detection. RAIM is designed to catch inconsistencies in range measurements and is thus useful in defeating a surreptitious lift off spoofing attack. Inconsistencies in a lift off attack exist when the spoof signal mixes with the genuine signal of similar power levels (within a few dB). The mixing creates some measurements from genuine signals and some from the spoofed signals. ARAIM cannot however mitigate across all categories of spoofers and hence should not represent a standalone spoofing solution. Although pre-and post-correlation signal processing is definitely the most efficient way to detect and mitigate spoofing effects, checking the measurements in the navigation domain is not a lost cause, as presented herein.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11367/72072
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