Joint Trajectory and Resource Allocation Optimization for Mobile Vehicles in UAV Assisted Secure ISAC System

Unmanned aerial vehicles (UAVs) are widely used for their flexibility and versatility, offering integrated sensing and communication (ISAC) services to mobile vehicles. However, the line-of-sight (LoS) links provided by the UAV are vulnerable to eavesdroppers. This paper designs a UAV-assisted ISAC secure model for mobile vehicles, where the source UAV (SUAV) detects vehicles and transmits information to RSUs, while the jamming UAV (JUAV) disrupts eavesdroppers (EVE) continuously. To measure the performance of detection, the radar estimation rate is presented from an information theory perspective. The worst-case secrecy rate is maximized by jointly optimizing ISAC task scheduling, power allocation, and SUAV trajectory under the constraints of anti-collision and signal-to-interference-plus-noise ratio (SINR).