Observations from using a portable LIDAR scanner to capture RF propagation modelling environments

Justin Worsey, I. Hindmarch, S. Armour, David R. Bull
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Abstract

Automated assessment of a 3D geographical environment is highly desirable for many reasons including the creation of accurate environments for RF propagation modelling tools to assist in network planning, and for the rapid deployment of communication aids in areas affected by war or natural disasters. This paper presents some of the observations and limitations of using a portable Laser Imaging, Detection and Ranging (LIDAR) scanner to capture the data points. The point cloud was subsequently classified using a deep learning network before being translated into mesh based environments. Observations include issues with the capturing technique, where a single person can be captured multiple times; a lack of scanner range which permitted false free space line-of-site (LOS) propagation and unexpected classification issues which impacted radio wave propagation. By addressing these observations, cheap and portable LIDAR scanners can provide a viable technique to assist network planning.
使用便携式激光雷达扫描仪捕捉射频传播建模环境的观察结果
由于许多原因,对3D地理环境的自动评估是非常可取的,包括为射频传播建模工具创建准确的环境,以协助网络规划,以及在受战争或自然灾害影响的地区快速部署通信辅助设备。本文介绍了使用便携式激光成像、探测和测距(LIDAR)扫描仪捕获数据点的一些观察结果和局限性。点云随后使用深度学习网络进行分类,然后将其转换为基于网格的环境。观察结果包括捕获技术的问题,一个人可以被捕获多次;缺乏扫描器范围,允许虚假的自由空间现场线(LOS)传播,以及影响无线电波传播的意外分类问题。通过处理这些观察结果,廉价便携的激光雷达扫描仪可以提供一种可行的技术来协助网络规划。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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