Secure Beamforming and Obstacle Avoidance Trajectory Design for UAV-Assisted ISAC

Unmanned aerial vehicles (UAVs), known for their high flexibility and maneuverability, are regarded as the aerial platforms of future integrated sensing and communication (ISAC) networks. The communication and sensing functions of ISAC share the same spectrum and signal waveform, which often results in communication information being embedded within the sensing waveforms, thereby increasing the risk of information leakage. To enhance the security of UAV-assisted ISAC, we propose a beamforming strategy based on the mutual cooperation between communication and sensing. Specifically, by utilizing the sensing function to process echo signals, we estimate the positions of potential eavesdroppers and obstacles, which supports subsequent obstacle avoidance trajectory planning and physical layer security design. To ensure the transmission secrecy, we introduce artificial noise into the system. By designing the UAV transmit beamforming and the covariance matrix of the artificial noise, we formulate an optimization problem that aims to minimize the signal-to-noise ratio (SNR) received by the eavesdropper. To address this non-convex optimization problem, we propose an optimization algorithm that combines Dinkelbach's transform and semidefinite relaxation (SDR). Simulation results demonstrate that the SNR of eavesdropper remains at a low level throughout the flight of UAV, validating the effectiveness of the proposed scheme.