Performance Assessment of Real-Time GNSS Spoofing Detection with IMU Measurements on Android Smartphones

GNSS spoofing poses a severe threat to smartphone users who heavily depend on real-time navigation service. With the adequate integration of embedded sensors, the adoption of GNSS/INS fusion navigation technology has become a promising strategy for safeguarding smartphone users. However, existing anti-spoofing techniques based on integrated navigation have not been rigorously evaluated over the common scenarios of everyday smartphone usage, which represents a primary application context for GNSS technology today. This research used three Mi 8 cellphones and one RedMi Note Pro 11, leveraging a loosely coupled Extended Kalman Filter (EKF) architecture and an innovation-based detection approach to counteract the prevalent single-transmitting antenna spoofing attacks. Within the sphere of influence of the spoofer, experiments were carried out in both stationary and dynamic contexts utilizing a custom-developed testing platform. This platform is capable of real-time collection of raw GNSS measurements and IMU data, and transmits it to the host machine, where the fusion calculation and the detection method are performed. The processed results are then displayed instantly, enabling simultaneous comparison and analysis of the detection performance among different devices. The results of this study offer a comprehensive analysis of the circumstances and causes that could deteriorate the actual performance of this method during practical testing, and affirm its efficacy and real-time detection capability in common usage scenarios for smartphone users. Moreover, the paper outlines the specific spoofing strategies that the innovation-based detection method can counter and delineates its protective range, providing solid data to underpin the wider application and progression of this technology.