A UWB-Based Indoor Positioning System Employing Neural Networks

被引：17
|
作者：
Li, Binghao [1 ]
Zhao, Kai [1 ]
Sandoval, Eduardo Benitez [2 ]
机构：
[1] Univ New South Wales, Sch Minerals & Energy Resources Engn, Sydney, NSW, Australia
[2] Univ New South Wales, Fac Art & Design, Sydney, NSW, Australia
来源：
JOURNAL OF GEOVISUALIZATION AND SPATIAL ANALYSIS | 2020年 / 4卷 / 02期
关键词：
Ultra-wideband (UWB); Indoor positioning; Neural network;
D O I：
10.1007/s41651-020-00059-2
中图分类号：
X [环境科学、安全科学];
学科分类号：
08 ; 0830 ;
摘要：
Because of its high time-domain resolution, ultra-wideband (UWB) technology is capable of precise range measurement and has been applied in many accurate indoor positioning systems. This paper presents a practical indoor positioning and navigation system using the UWB modules we developed based on Decawave UWB chipset. In order to enhance the performance of the system in NLOS scenarios, a neural network approach is integrated. The feasibility of the combined approach is analysed and its accuracy is evaluated. The experiment results indicate that the neural network can maintain a stable accuracy no matter whether it is in an NLOS scenario and it is capable to identify the locations on two trajectories which are next to each other with very high confidence.
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页数：9
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