Indoor Positioning System (IPS) Using Ultra-Wide Bandwidth (UWB)-For Industrial Internet of Things (IIoT)

被引：32

作者：

Che, Fuhu ^{[1
]}

Ahmed, Qasim Zeeshan ^{[1
]}

Lazaridis, Pavlos I. ^{[1
]}

Sureephong, Pradorn ^{[2
]}

Alade, Temitope ^{[3
]}

机构：

[1] Univ Huddersfield, Dept Comp & Engn, Huddersfield HD1 3DH, England

[2] Chiang Mai Univ, Coll Arts Media & Technol, Chiang Mai 50200, Thailand

[3] Nottingham Trent Univ, Sch Sci & Technol, Dept Comp Sci, Nottingham NG11 8NS, England

来源：

SENSORS | 2023年 / 23卷 / 12期

关键词：

UWB; indoor positioning system; localization; machine learning; NLoS; TO-UAV COMMUNICATIONS; ERROR-CORRECTION; MULTIPLE-ACCESS; NEURAL-NETWORKS; IMPULSE RADIO; UWB; LOCALIZATION; ANTENNA; SENSOR; CLASSIFICATION;

D O I：

10.3390/s23125710

中图分类号：

O65 [分析化学];

学科分类号：

070302 ; 081704 ;

摘要：

The integration of the physical and digital world has become increasingly important, and location-based services have become the most sought-after application in the field of the Internet of Things (IoT). This paper delves into the current research on ultra-wideband (UWB) indoor positioning systems (IPS). It begins by examining the most common wireless communication-based technologies for IPSs followed by a detailed explanation of UWB. Then, it presents an overview of the unique characteristics of UWB technology and the challenges still faced by the IPS implementation. Finally, the paper evaluates the advantages and limitations of using machine learning algorithms for UWB IPS.

引用

页数：29

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