A Heading Correction Method for UAV Swarms Against Yaw Deception Based on the Consensus Potential Field

A yaw spoofing heading correction method utilizing a consensus force field is introduced to address the issue of drone swarm heading deviation during Global Navigation Satellite System GNSS spoofing attacks. Firstly, a noisy environment based on asymmetric information environment is established to simulate the attack and defense scenario of unmanned aerial vehicle clusters against yaw deception attacks under environmental noise interference. Then, based on the attack principle, the yaw correction problem is transformed into an artificial potential field problem where the repulsive field is invisible, and the repulsive source is predicted based on spatial relationships to achieve pre-liminary correction of the yaw direction Finally, by designing a lightweight gamma Consensus mechanism and further correcting the yaw direction through credibility calculation and consensus mechanism, collaborative de-fense against yaw deception attacks is achieved. The experimental results in-dicate that, Under the CPF method, the cluster achieved a destination error of 10.32 meters, a trajectory deviation of 13.35 meters, and a task comple-tion rate of 90.45 . Compared with game models, random decision, and other methods, there is a significant improvement, which verifies the effec-tiveness and robustness of the method in the face of yaw deception attacks in long-distance flight missions.