Unmanned aerial vehicles (UAVs) can be utilized as relay platforms to assist maritime wireless communications. However, complex channels and multipath effects at sea can adversely affect the quality of UAV transmitted signals. Collaborative beamforming (CB) can enhance the signal strength and range to assist the UAV relay for remote maritime communications. However, due to the open nature of UAV channels, security issue requires special consideration. This paper proposes a dual UAV cluster-assisted system via CB to achieve physical layer security in maritime wireless communications. Specifically, one UAV cluster forms a maritime UAV-enabled virtual antenna array (MUVAA) relay to forward data signals to the remote legitimate vessel, and the other UAV cluster forms an MUVAA jammer to send jamming signals to the remote eavesdropper. In this system, we formulate a secure and energy-efficient maritime communication multi-objective optimization problem (SEMCMOP) to maximize the signal-to-interference-plus-noise ratio (SINR) of the legitimate vessel, minimize the SINR of the eavesdropping vessel and minimize the total flight energy consumption of UAVs. Since the SEMCMOP is an NP-hard and large-scale optimization problem, we propose an improved swarm intelligence optimization algorithm with chaotic solution initialization and hybrid solution update strategies to solve the problem. Simulation results indicate that the proposed algorithm outperforms other comparison algorithms, and it can achieve more efficient signal transmission by using the CB-based method.

翻译：无人机可作为中继平台辅助海上无线通信。然而，海上复杂的信道和多径效应会对无人机传输信号的质量产生不利影响。协作波束成形能够增强信号强度与覆盖范围，从而辅助无人机中继实现远距离海上通信。但由于无人机信道的开放性，安全性问题需要特别考虑。本文提出一种基于协作波束成形的双无人机集群辅助系统，以实现海上无线通信的物理层安全。具体而言，一个无人机集群构成海上无人机虚拟天线阵列中继，将数据信号转发至远处的合法船只；另一个无人机集群构成海上无人机虚拟天线阵列干扰器，向远处的窃听者发送干扰信号。在该系统中，我们构建了一个安全且节能的海上通信多目标优化问题，旨在最大化合法船只的信干噪比、最小化窃听船只的信干噪比，并最小化无人机的总飞行能耗。由于该问题属于NP难且大规模优化问题，我们提出了一种改进的群体智能优化算法，该算法采用混沌解初始化与混合解更新策略来求解该问题。仿真结果表明，所提算法性能优于其他对比算法，并且能够通过基于协作波束成形的方法实现更高效的信号传输。