UAV-RHS-Enabled Full-Duplex ISAC Covert System: Robust Beamforming and Trajectory Optimization

This paper proposes a novel covert transmission framework for an unmanned aerial vehicle (UAV)-reconfigurable holographic surface (RHS)-aided full-duplex (FD) integrated sensing and communication (ISAC) system, where the aerial access point (AP) simultaneously performs target sensing and downlink covert communication. We jointly design the AP’s downlink transmit signal and uplink receive beamformers, the RHS weights, the users’ uplink transmit powers, and the UAV’s trajectory, considering imperfect knowledge of the warden’s channel state information (CSI). An optimization problem is formulated to maximize the minimum covert transmission rate (CTR) among all downlink covert users (DCUs), subject to constraints on required sensing and uplink transmission capabilities, covertness, and total power budget. To tackle the intractable non-convex problem, we leverage the Bernstein-type inequality, majorization-minimization (MM), and successive convex approximation (SCA), and propose a secure optimization framework that efficiently updates all variables using convex optimization techniques. To further understand the proposed algorithm, its convergence behavior and computational complexity are discussed. Simulation results demonstrate that integrating RHS and UAV techniques into the optimization design enhances the covert transmission performance of FD-ISAC systems while ensuring a certain level of sensing capability.