Joint Trajectory and Beamforming Optimization for UAV-ISAC Secure Communications

Integrated Sensing and Communication (ISAC) can assist Uncrewed Aerial Vehicle (UAV) secure communications by acquiring information about eavesdroppers. However, existing studies have not systematically investigated ISAC beamforming for simultaneously sensing the channel information of ground eavesdroppers, jamming eavesdropping links, and communicating with users, which poses significant challenges in ensuring both sensing accuracy and communication confidentiality. To address this issue, we propose a UAV-ISAC secure communication algorithm to maximize average secrecy rate by jointly optimizing communication and sensing beamforming, user scheduling, sensing time allocation, and UAV trajectory. We address the formulated NP-hard problem by decomposed it into three subproblems. We first relax binary user scheduling and sensing time allocation by a penalty-based successive convex approximation approach. The UAV trajectory is then iteratively optimized while beamforming is designed using semidefinite relaxation, with matrix lifting applied to handle the rank-one constraint. A triple-layer iterative algorithm is constructed by integrating these steps to achieve a suboptimal solution. Numerical experiment results and theoretical analysis validate the superiority of the proposed algorithm in terms of average secrecy rate, convergence and computational complexity.