@article{WU2025, 
author = {Jun WU and Weijie YUAN and Qin TAO and Hongjia HUANG and Derrick Wing Kwan NG},
title = {Aerial-networked ISAC-empowered collaborative energy-efficient covert communications☆},
year = {2025},
journal = {Chinese Journal of Aeronautics},
volume = {38},
number = {10},
keywords = {Integrated sensing and communication, Unmanned aerial vehicles, Low-altitude economy, Trajectory design, Jammer selection},
url = {https://www.sciopen.com/article/10.1016/j.cja.2025.103451},
doi = {10.1016/j.cja.2025.103451},
abstract = {Covert unmanned aerial vehicle (UAV) communication has garnered considerable attention in wireless systems for realizing the sustainable low-altitude economy (LAE). This paper investigates the system policy, trajectory design, and resource allocation for energy-efficient aerial networked systems with the aid of an integrated sensing and communications (ISAC) framework, in which multiple UAVs are employed to simultaneously conduct cooperative sensing and covert downlink transmissions to multiple ground users (GUs) in the presence of a mobile warden (Willie). Specifically, to improve the communication covertness, UAVs are strategically switched between jamming (JUAV) and information (IUAV) modes. Additionally, to cope with the mobility of Willie, an unscented Kalman filtering (UKF)-based method is employed to track and predict Willie’s location relying on the delay and Doppler measurements extracted from the ISAC echoes. Capitalizing on the predicted Willie’s location, a real-time energy efficiency (EE) maximization problem is formulated by jointly optimizing the JUAV selection strategy, IUAV-GU scheduling, communication/jamming power allocation, and UAV trajectories design. The formulation takes into account the communication covertness requirement and the maximum transmit power budget, leading to a mixed-integer non-convex fractional programming. To tackle this challenge, the alternating optimization (AO) approach is adopted, which decomposes the original problem into a series of sub-problems, allowing us to obtain an efficient sub-optimal solution. Simulation results demonstrate that the proposed scheme is capable of tracking Willie accurately and offering excellent system EE performance compared to various benchmark schemes adopting existing designs.}
}