On Secure UAV-Aided ISAC System via Sensing

Integrated sensing and communication (ISAC) is a rapidly evolving and highly promising technology for wireless networks, enabling the concurrent execution of communication and sensing functions within constrained spectrum resources. This article examines a secure ISAC system assisted by an uncrewed aerial vehicle (UAV), in which the extended Kalman filter (EKF) is incorporated for accurate estimation and prediction of eavesdropper states. Radar signals are transmitted to track and jam potential eavesdroppers, while communication services are simultaneously provided to ground users. Under practical constraints—including maximum UAV velocity, transmit power, and propulsion energy consumption—the achievable uplink rate is maximized through joint optimization of the transmit beamforming and UAV trajectory. To address the computationally complex and inherently non-convex optimization problem, an efficient iterative algorithm combining block coordinate descent (BCD) with successive convex approximation (SCA) is designed, yielding a high-quality suboptimal solution. Finally, comprehensive simulations are conducted to evaluate the effectiveness of the proposed scheme against benchmark methods and to elucidate the inherent trade-off between communication and sensing performance.