Secure Rate Maximization for IRS-UAV Systems with Integrated Sensing and Communication

With the rapid advancement of communication technologies, spectrum resources have become increasingly scarce, prompting the development of integrated sensing and communication (ISAC) technology. However, the inherent openness of wireless channels makes transmitted information vulnerable to interference and eavesdropping, posing significant security challenges. Most existing studies focus on specific technologies or scenarios without offering comprehensive and systematic solutions. To address these limitations, we propose a secure ISAC system for unmanned aerial vehicle (UAV) assisted by intelligent reflecting surfaces (IRS). By jointly optimizing the IRS phase shift, active beamforming, UAV trajectory, and artificial noise (AN) allocation, the system secrecy rate is maximized while satisfying signal-to-noise ratio (SNR) and signal-to-interference-plus-noise ratio (SINR) constraints. We propose an iterative alternating optimization (AO) algorithm that decomposes the problem into three convex sub-problems, each solved efficiently. Simulation results demonstrate that the algorithm significantly improves transmission security and sensing performance, effectively mitigates eavesdropping, and provides a robust solution for ISAC system security.