Phase design and trajectory optimization of IRS-assisted UAV-ISAC system

In this paper, an integrated sensing and communication (ISAC) system with intelligent reflector assistance (IRS) in the unmanned aerial vehicle (UAV) scene is studied. For the system, the optimization problem of maximizing the minimum beam gain at the desired sensing angle of the target is proposed under the constraints of the signal-to-noise ratio (SNR), the maximum transmit power of the UAV and the trajectory of the UAV to ensure the normal communication with the ground user. An enhanced reinforcement learning algorithm is used to optimize the UAV trajectory and solve the problem. The simulation results show that the performance of UAV-ISAC system deployed by IRS has certain advantages, and the perception performance can be improved.