照明:利用无处不在的可见光和COTS设备进行室内定位

Yiqing Hu, Yan Xiong, Wenchao Huang, Xiangyang Li, Yanan Zhang, Xufei Mao, Panlong Yang, Caimei Wang
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引用次数: 15

摘要

在本文中,我们提出了一种新的室内定位方案,Lightitude,利用无处不在的可见光,这是必要的和密集的部署在几乎所有的室内环境。与现有的利用特殊led的定位系统不同,无处不在的可见光缺乏能够唯一识别光源的指纹,这导致了RLS可能对应多个候选位置的模糊性问题。此外,接收光强(RLS)不仅取决于设备的位置,而且受其方向的严重影响,这给现场测量带来了很大的复杂性。为了解决这些问题,我们首先提出并验证了一个现实的光强度模型,以避免昂贵的现场调查,然后利用用户的移动性来生成空间相关的RLS,以解决单个RLS的位置模糊问题。实验结果表明,在办公场景(720m2)和图书馆场景(960m2)下,lightity的平均精度分别为1.93m和2.24m。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Lightitude: Indoor Positioning Using Ubiquitous Visible Lights and COTS Devices
In this paper, we propose a novel indoor localization scheme, Lightitude, by exploiting ubiquitous visible lights, which are necessarily and densely deployed in almost all indoor environments. Different from existing positioning systems that exploit special LEDs, ubiquitous visible lights lack fingerprints that can uniquely identify the light source, which results in an ambiguity problem that an RLS may correspond to multiple candidate positions. Moreover, received light strength (RLS) is not only determined by device's position, but also seriously affected by its orientation, which causes great complexity in site-survey. To address these challenges, we first propose and validate a realistic light strength model to avoid the expensive site-survey, then harness user's mobility to generate spatial-related RLS to tackle single RLS's position-ambiguity problem. Experiment results show that Lightitude achieves mean accuracy 1.93m and 2.24m in office (720m2) and library scenario (960m2) respectively.
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