Unmanned aerial vehicle (UAV)-enabled integrated sensing and communication (ISAC) is regarded as a key enabler for next-generation wireless systems. However, conventional fixed antenna arrays limit the ability of UAVs to fully exploit their inherent potential. To overcome this limitation, we propose a UAV-enabled ISAC framework equipped with fluid antenna (FA) arrays, where the mobility of antenna elements introduces additional spatial degrees of freedom to simultaneously enhance communication and sensing performance. A multi-objective optimization problem is formulated to maximize the communication rates of multiple users while minimizing the Cram\'er-Rao bound (CRB) for single-target angle estimation. Due to excessively frequent updates of FA positions may lead to response delays, a three-timescale optimization framework is developed to jointly design transmit beamforming, FA positions, and UAV trajectory based on their characteristics. To solve the non-convexity of the problem, an alternating optimization-based algorithm is developed to obtain a sub-optimal solution. Numerical results show that the proposed scheme significantly outperforms various benchmark schemes, validating the effectiveness of integrating the FA technology into the UAV-enabled ISAC systems.

翻译：无人机使能的通感一体化被视为下一代无线系统的关键使能技术。然而，传统的固定天线阵列限制了无人机充分发挥其固有潜力的能力。为克服这一限制，本文提出一种配备流体天线阵列的无人机使能通感一体化框架，其中天线单元的移动性引入了额外的空间自由度，以同时增强通信与感知性能。我们构建了一个多目标优化问题，旨在最大化多用户的通信速率，同时最小化单目标角度估计的克拉美-罗下界。考虑到流体天线位置更新过于频繁可能导致响应延迟，本文基于各变量的特性，开发了一个三时间尺度优化框架，以联合设计发射波束成形、流体天线位置与无人机轨迹。为解决问题的非凸性，开发了一种基于交替优化的算法以获得次优解。数值结果表明，所提方案显著优于多种基准方案，验证了将流体天线技术集成到无人机使能通感一体化系统中的有效性。