Integrated sensing and communication (ISAC) has emerged as a promising key technology for future wireless networks, enabling the efficient coordination of sensing and communication functions within limited resources. This work investigates a secure ISAC system assisted by an uncrewed aerial vehicle (UAV). By incorporating the extended Kalman filter (EKF), the proposed system is capable of delivering communication services to legitimate users while simultaneously jamming eavesdroppers and performing joint prediction and tracking of the trajectories of both legitimate and illegitimate users. Considering practical constraints such as {sensing beamwidth}, transmit power, and UAV's propulsion energy consumption, the secrecy rate is maximized through the joint design of transmit beamforming and UAV trajectory. To tackle the resulting highly non-convex optimization problem, an efficient iterative algorithm is developed by integrating block coordinate descent, successive convex approximation, and EKF, thereby yielding a high-quality suboptimal solution. Extensive simulation results validate the superior performance of the proposed scheme compared to benchmarks.

翻译：通信感知一体化（ISAC）已成为未来无线网络的关键技术，能够在有限资源内高效协同感知与通信功能。本文研究了一种无人机辅助的安全ISAC系统。通过引入扩展卡尔曼滤波（EKF），所提系统能够在为合法用户提供通信服务的同时，对窃听者实施干扰，并对合法与非合法用户的轨迹进行联合预测与跟踪。考虑感知波束宽度、发射功率及无人机推进能耗等实际约束，通过联合设计发射波束成形与无人机轨迹，最大化保密速率。针对由此产生的高度非凸优化问题，本文提出了一种融合块坐标下降法、逐次凸近似与EKF的高效迭代算法，从而获得高质量次优解。大量仿真结果验证了所提方案相较于基准方法的优越性能。