论文标题
对具有5G未来视角的空中和地面机器人的基于射频的本地化的综述
A Review of Radio Frequency Based Localization for Aerial and Ground Robots with 5G Future Perspectives
论文作者
论文摘要
有效的本地化在许多现代化的地面车辆（UGV）和无人驾驶汽车（UAVS）的现代应用中起着至关重要的作用，这将有助于改善控制，安全性，电力经济性等。无处不在的5G NR（新无线电）蜂窝网络将为增强UAV和UGV的本地化提供新的机会。在本文中，我们回顾了基于射频（RF）的定位方法。我们回顾可用于本地化的RF功能，并调查适用于两个一般类别下的无人车辆的当前方法：基于范围和指纹。研究了有关无人机和UGV的基于RF的本地化的现有最新文献，并探索了预设定位的5G NR，以增强本地化的局部化，并探讨了未来的研究方向。
Efficient localization plays a vital role in many modern applications of Unmanned Ground Vehicles (UGV) and Unmanned aerial vehicles (UAVs), which would contribute to improved control, safety, power economy, etc. The ubiquitous 5G NR (New Radio) cellular network will provide new opportunities for enhancing localization of UAVs and UGVs. In this paper, we review the radio frequency (RF) based approaches for localization. We review the RF features that can be utilized for localization and investigate the current methods suitable for Unmanned vehicles under two general categories: range-based and fingerprinting. The existing state-of-the-art literature on RF-based localization for both UAVs and UGVs is examined, and the envisioned 5G NR for localization enhancement, and the future research direction are explored.
