Session A2: GNSS Security: Interference, Jamming, and Spoofing 1

Navigating Interference - Examining In-Flight GNSS Spoofing Patterns and Signal Disruptions
Michael Felux, Valentin Fischer, Sophie Jochems, Benoit Figuet, and Raphael Monstein, ZHAW - Zurich University of Appl. Sci.
Location: Beacon A
Date/Time: Wednesday, Jan. 29, 9:43 a.m.

Peer Reviewed

In this study, we present an analysis of GNSS signals collected in-flight on a scheduled commercial flight out of Amman (AMM), Jordan in September 2024. The flight crew took a commercial receiver capable of tracking multiple GNSS constellations and frequencies and recorded GNSS signals from behind the window inside the flight deck. The flight route crossed Jordanian and Egyptian airspace, two regions known to be affected by GNSS spoofing during the period of the flight. While the reception quality of the receiver inside the cockpit was not ideal, findings show that the receiver was subject to spoofing. While on a southerly heading still in Jordanian airspace, the estimated position jumped back to the airport of Amman where the flight departed. This was true for the signals of GPS and GLONASS. Signal reception for Galileo and BeiDou was degraded but the remaining signals did not appear to be spoofed. While subject to spoofing signals of GPS were only received on the L1 frequency, no signals on L5/E5a were tracked by the receiver. The navigation messages were not altered, only the pseudoranges were inconsistent with the true position of the aircraft. In addition to the GNSS data, we analyzed Automatic Dependent Surveillance-Broadcast (ADS-B) data from the same flight to explore the correlation between GNSS spoofing and the performance of ADS-B, focusing on the availability of position messages and the associated navigation accuracy and integrity metrics, such as Navigation Accuracy Category for Position (NACp) and Navigation Integrity Category (NIC). While showing degrading ADS-B integrity parameters consistent with jamming, the aircraft position did not appear as spoofed in the analyzed data.