Covert UAV Directional Spoofing Algorithm Evading Multiple Anti-Spoofing Techniques

The proliferation of unmanned aerial vehicle (UAV) applications in contemporary society has introduced significant security vulnerabilities. While existing spoofing methodologies can deceive UAVs into deviating from preset trajectories by manipulating global navigation satellite system (GNSS) signals, their practical efficacy remains constrained by prevalent anti-spoofing mechanisms. This study proposes an innovative covert directional spoofing framework designed to circumvent advanced anti-spoofing systems, including Kalman filter innovation-based monitoring, least-squares residual receiver autonomous integrity monitoring (LSR-RAIM), and parameter rationality checks. The spoofing algorithm incorporates UAV dynamics and navigation models, with radar employed to measure the UAV's real-time position and velocity. Mathematical models of anti-spoofing algorithms are constructed, and the range of spoofing measurements that can avoid detection is established. The spoofing algorithm needs to know the preset trajectory of the target UAV and gradually changes the direction of UAV. A closed-loop spoofing strategy is introduced to dynamically adjust the deceptive gain matrix and modify counterfeit measurements. Experimental results demonstrate the algorithm's capability to successfully divert a UAV 230 meters from designated flight paths while inducing a 5° northward directional deviation within 250 seconds. Minor fluctuations in Kalman innovation, navigation parameters, and sensor zero biases were observed during the spoofing attack. The proposed algorithm demonstrates reliable capability in directing UAVs along predetermined spoofing trajectories while remaining undetectable to integrated anti-spoofing mechanisms.