Path following identification of unmanned aerial vehicles for navigation spoofing and its application

As unmanned aerial vehicles (UAVs) use global navigation satellite systems for positioning, the openness and weak security of satellite navigation signals make these systems easily falsifiable. By leveraging these characteristics, we propose a path following identification algorithm to gain control of UAVs using navigation spoofing as a countermeasure against illegal activities. Our contribution is threefold. First, we redefine the UAV kinematics model by treating the spoofing signal as wind. Subsequently, the relation between the spoofing signal and UAV heading angle is identified based on a path following algorithm, and the relation accuracy is experimentally verified. Finally, we propose the spoofing sparse A* search (SSAS) algorithm, whose effectiveness is verified by simulations of a UAV directed to a designated area while avoiding obstacles and forbidden areas.