Satellite-Assisted UAV Trajectory Control in Hostile Jamming Environments

Satellite and unmanned aerial vehicle (UAV) networks have been introduced as enhanced approaches to provide dynamic control, massive connections and global coverage for future wireless communication systems. This paper considers a coordinated satellite-UAV communication system, where the UAV performs the environmental reconnaissance task with the assistance of satellites in a hostile jamming environment. To fulfill this task, the UAV needs to realize autonomous trajectory control and upload the collected data to the satellite. With the aid of the uploading data, the satellite builds the environment situation map integrating the beam quality, jamming status, and traffic distribution. Accordingly, we propose a closed-loop anti-jamming dynamic trajectory optimization approach, which is divided into three stages. Firstly, a coarse trajectory planning is made according to the limited prior information and preset points. Secondly, the flight control between two adjacent preset points is formulated as a Markov decision process, and reinforcement learning (RL) based automatic flying control algorithms are proposed to explore the unknown hostile environment and realize autonomous and precise trajectory control. Thirdly, based on the collected data during the UAV's flight, the satellite utilizes an environment situation estimating algorithm to build an environment situation map, which is used to reselect the preset points for the first stage and provide better initialization for the RL process in the second stage. Simulation results verify the validity and superiority of the proposed approach.