A Spoofing Detection and Direction-Finding Approach for Global Navigation Satellite System Signals Using Off-the-Shelf Anti-Jamming Antennas

Global Navigation Satellite System (GNSS) spoofing induces the target receiver to obtain the wrong positioning and timing results, which is very harmful. It is necessary to develop high-precision GNSS spoofing detection and associated direction-finding methods. In order to achieve sensitive and high-precision direction-finding for GNSS spoofing, it is necessary to realize the spoofing signal detection in the capture phase. This paper first proposes a method of GNSS spoofing detection, based on machine learning, that extracts features in the capture phase, which realizes various types of spoofing detection such as matching power, carrier phase alignment, and frequency locking. Notably, existing spoofing-direction-finding methods are mainly based on dedicated antenna arrays, which incur high costs and are not conducive to large-scale deployments. The basis of the spoofing detection proposed by this paper consists of a differential phase-center correction method, which is proposed in the context of an off-the-shelf anti-jamming array antenna, which effectively reduces the impact of the phase-center jitter introduced by the mutual coupling between antenna arrays on the direction-finding. The publicly accessible Texas Spoofing Test Battery (TEXBAT) dataset and actual measured data are both used for test verification. The results demonstrate that the proposed spoofing detection method can achieve success rates of over 97% on the TEXBAT dataset and more than 96% on the measured dataset, and the accuracy of the proposed direction-finding method can reach 1°, which can realize the effective detection and direction-finding of GNSS spoofing.