LOS and NLOS identification based on UWB stable distribution

M. Tabaa, C. Diou, M. El Aroussi, B. Chouri, A. Dandache
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引用次数: 12

Abstract

Ultra-wideband (UWB) technology for the localization of wireless sensor networks has received considerable attention last few years. This technology is dedicated for indoor localization using a fine delay of resolution and obstacle-penetration capabilities. A lot of challenges remain before implementation of UWB can be deployed on a large scale like non-line-of-sight (NLOS which is especially critical for most location-based applications because the NLOS propagation introduces positive bias in the estimation of distance, which can seriously affect the performance of localization.In this paper, we present a technique for identifying between both line-of-sight(LOS) and non-line-of-sight (NLOS) contexts based on stable distribution parameters using SVM (Support Vector Machine) methods for classification. This characterization was applied to UWB measurements collected from whyless.com project by the IMST group, over bandwidth of 10 GHz.
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基于超宽带稳定分布的LOS和NLOS识别
近年来,超宽带(UWB)无线传感器网络定位技术受到了广泛关注。该技术专门用于室内定位,使用精细的分辨率延迟和障碍物穿透能力。在实现超宽带大规模部署之前还有很多挑战,比如非视距(NLOS),这对于大多数基于位置的应用来说尤其重要,因为非视距传播会在距离估计中引入正偏置,这会严重影响定位性能。在本文中,我们提出了一种基于稳定分布参数的视距(LOS)和非视距(NLOS)上下文识别技术,该技术使用支持向量机(SVM)方法进行分类。这一特性被应用于IMST小组从whyless.com项目收集的超宽带测量,带宽超过10 GHz。
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