A UWB-Based Indoor Positioning System Employing Neural Networks

被引:0
作者
Binghao Li
Kai Zhao
Eduardo Benitez Sandoval
机构
[1] University of New South Wales,School of Minerals and Energy Resources Engineering
[2] University of New South Wales,Faculty of Art and Design
来源
Journal of Geovisualization and Spatial Analysis | 2020年 / 4卷
关键词
Ultra-wideband (UWB); Indoor positioning; Neural network;
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学科分类号
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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