NM-LUD: A NLOS Mitigation Method with Low-cost UWB Devices for Indoor Positioning

Tong Wu, Han Li, Bo Gao, Ke Xiong, Pingyi Fan, K. Letaief
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Abstract

Ultra-wideband (UWB) is a popular technology for indoor positioning. However, non-line-of-sight (NLOS) propagation caused by human occlusion dramatically affects the accuracy of UWB-based indoor positioning. Most of the existing works focused on mitigating NLOS errors in the scenarios with building structure occlusion, but the NLOS mitigation under human occlusion has not been well addressed. To this end, this paper aims to mitigate the NLOS impact of human occlusion, and then proposes a method of NLOS mitigation to reduce NLOS ranging errors under human occlusion with low-cost UWB devices (i.e., NM-LUD). It takes a set of signal features extracted from low-cost devices as input, calculates their weights and mitigates the ranging error based on the features' weights. Experiment results on the two data sets collected by LinkTrack S and UML1 UWB devices show that the method reduces ranging error from 0.9009 m to 0.1435 m (about by 84.07%) and from 0.7466 m to 0.0792 m (about by 89.39%) respectively, which greatly mitigates the influence of NLOS caused by human occlusion.
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NM-LUD:一种利用低成本超宽带设备进行室内定位的NLOS缓解方法
超宽带(UWB)是一种流行的室内定位技术。然而,人眼遮挡引起的非视距(NLOS)传播极大地影响了基于uwb的室内定位精度。现有的大部分工作都集中在减少建筑物结构遮挡情况下的NLOS误差上,但人类遮挡情况下的NLOS缓解问题尚未得到很好的解决。为此,本文以减轻人为遮挡对NLOS的影响为目标,提出了一种利用低成本超宽带设备(即NM-LUD)降低人为遮挡下NLOS测距误差的NLOS缓解方法。它从低成本设备中提取一组信号特征作为输入,计算特征的权重,并根据特征的权重减轻测距误差。在LinkTrack S和UML1 UWB设备采集的两个数据集上的实验结果表明,该方法将测距误差分别从0.9009 m到0.1435 m(约降低84.07%)和0.7466 m到0.0792 m(约降低89.39%),大大减轻了人为遮挡引起的NLOS影响。
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