ISAC中基于UAV与IRS辅助的感知性能优化方案OA

In integrated sensing and communication(ISAC)systems,when a base station cannot establish a reliable direct link with sensing targets,system performance is significantly degraded.To address this issue,this paper proposes a sensing performance optimization scheme assisted by unmanned aerial vehicles(UAVs)and intelligent reflecting surfaces(IRS).The UAV acquires information from ground nodes through line-of-sight links and IRS-reflected links,and then forwards the information to the base station.During the entire flight period,under the constraint that the sensing performance and communication rate for each node exceed predefined thresholds,the proposed scheme jointly optimizes UAV task scheduling,transmit power,trajectory,and IRS phase shifts to maximize overall sensing performance and data rate.The resulting non-convex optimization problem is decomposed into four subproblems,which are solved iteratively using successive convex approximation and relaxation methods to obtain a suboptimal solution.Simulation results demonstrate that the proposed optimization scheme effectively maximizes both sensing performance and communication rate,and further confirm that IRS can significantly enhance the sensing capability of UAVs.