低空空域无线网络中的感知：系统、技术与发展
Sensing in Low-altitude Wireless Networks: Systems, Techniques, and Developments
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中文总结 AI 辅助
本文针对低空空域无线网络（LAWN）的感知需求，系统综述其系统框架、核心技术与未来方向，还给出多模态感知案例，提供更全面针对性的LAWN感知综述。
中文摘要 AI 辅助
低空空域具有高度动态性和对安全性要求极高的特点，这使得感知成为低空空域无线网络（LAWN）不可或缺的组成部分。尽管感知技术已在多种范式下得到广泛研究，但最先进的感知方案与LAWN的实际感知需求之间仍存在显著差距。为填补这一研究空白，本文从系统框架、核心技术和研究趋势三个维度对面向LAWN的感知进行了系统综述。具体而言，本文首先分析了LAWN感知的系统框架，涵盖LAWN感知的概念、服务与任务、节点与目标以及场景；接着，从传播介质、协作、方法和模态的角度对现有感知技术进行了对比分析，探讨了它们的优势与局限性；随后，总结了可部署LAWN感知系统的有前景的未来研究方向，涵盖非协作与协作感知、模型驱动与数据驱动感知，以及模型与数据驱动的多模态感知；最后，本文给出了一个用于实时空中目标感知的模型与数据驱动多模态方法的案例研究。与现有关于LAWN或感知的综述相比，本文提供了更全面、更具针对性的综述，专门聚焦于LAWN感知。
英文摘要
The highly dynamic and safety-critical characteristics of low-altitude airspace render sensing an indispensable component of low-altitude wireless networks (LAWN). Although sensing techniques have been extensively studied under diverse paradigms, a prominent mismatch persists between state-of-the-art sensing schemes and the practical sensing demands of LAWN. To fill this research gap, this article systematically reviews LAWN-oriented sensing from the dimensions of system framework, core technologies, and research trends. Specifically, we first analyze the sensing system framework, covering concepts, services and tasks, nodes and targets, and scenarios for LAWN sensing. Next, we conduct a comparative analysis of existing sensing techniques from the perspectives of propagation medium, cooperation, methodology, and modality, analyzing their advantages and limitations. Then, we summarize promising future research directions for deployable LAWN sensing systems, covering non-cooperative and cooperative sensing, model-driven and data-driven sensing, and model-and-data-driven multi-modal sensing. Finally, we present a case study of a model-and-data-driven multi-modal method for real-time aerial target sensing. Compared with existing surveys on LAWN or sensing, this article delivers a more comprehensive, targeted review exclusively centered on LAWN sensing.
