On Secure EKF-enhanced UAV-ISAC Systems
2026-06-02 • Information Theory
Information Theory
AI summaryⓘ
The authors study a system where a flying drone (UAV) helps both communicate with good users and block bad users trying to listen in. They use a method called the extended Kalman filter to track where everyone is going while managing the drone's power and signal direction. Their goal is to send messages securely by planning the drone's path and signal carefully. They create a special algorithm to solve this tricky problem and show through simulations that their approach works better than existing ones.
Integrated sensing and communication (ISAC)Uncrewed aerial vehicle (UAV)Extended Kalman filter (EKF)Secrecy rateTransmit beamformingTrajectory optimizationBlock coordinate descentSuccessive convex approximationEavesdropping
Authors
Hongjiang Lei, Heng Jin, Ki-Hong Park, Jia Ye, Liang Yang, Gaofeng Pan, Yun Li
Abstract
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.