UAV Trajectory Control Against Hostile Jamming in Satellite-UAV Coordination Networks

Large unmanned aerial vehicle (UAV) performs reconnaissance and data collection missions against hostile jamming in satellite-UAV coordination Networks. In this case, the ground base station (BS) is unable to provide access service to the UAV, thus the UAV has to rely on information support from the satellite communication system. Low earth orbit (LEO) satellites provide access beams for UAVs, and the UAV transmits the collected data to the satellite via uplink. Due to the unknown and uncertain environment, it is difficult for large UAV to get an effective planned flight trajectory, and the presence of malicious jamming further exacerbates the complexity of trajectory control. To address this problem, a reinforcement learning (RL) based trajectory control approach is proposed to explore the unknown jamming environment and realize autonomous trajectory planning. Finally, the simulation results prove the effectiveness of the proposed approach.