Early Detection of Coherent GNSS Spoofing Attacks with Cluster Analysis at Receiver Acquisition Stage

Resilience of Global Navigation Satellite System (GNSS) usage against spoofing attacks can be increased by signal monitoring algorithms aiming to detect a spoofing signal at the acquisition stage of GNSS receiver signal processing. A common approach is to search for the presence of multiple correlation peaks in the absolute value of the Cross-Ambiguity Function (CAF). In this context, it is particularly challenging to detect spoofing signals with a correlation peak closely aligned to that of the authentic signal, as is the case at the early stage of a coherent spoofing attack. In the present work, a spoofing detection method is proposed that monitors the magnitude of the CAF by means of clustering techniques. It is designed to detect the pull-off during a coherent power-matched spoofing attack already at an early stage. The method is evaluated for the GPS L1 C/A signal based on a static scenario of the Texas Spoofing Test Battery (TEXBAT) data set as well as for the Galileo E1-B signal based on a real-world digital snapshot recording in the E1 frequency band which is augmented by emulated spoofing signals at the level of digital signal processing.