Research on indoor positioning system algorithm based on UWB technology

被引:0
|
作者
Ma, Weimin [1 ]
Fang, Xianbao [2 ]
Liang, Li [1 ]
Du, Jianghuai [1 ]
机构
[1] Anhui Vocational and Technical College, Anhui, Hefei,230011, China
[2] Shanghai Xinyuan Microenterprise Development Co., Ltd, Shanghai,201306, China
来源
Measurement: Sensors | 2024年 / 33卷
关键词
Energy utilization - Indoor positioning systems - Kalman filters - Ultra-wideband (UWB);
D O I
10.1016/j.measen.2024.101121
中图分类号
学科分类号
摘要
Ultra wideband (UWB) indoor positioning technology is attracting significant attention in the present realm of indoor wireless positioning technology due to its numerous advantages, including low energy consumption, exceptional wireless transmission rates, remarkable resolution, and powerful anti-interference capabilities.This paper applies the time of arrival (TOA) location technique, derived from the research on UWB location method, to calculate the distance between the base station and the tag using the signal flight time. By incorporating the bilateral two-way ranging algorithm, the system has been fine-tuned to lower the precision demands on the hardware.A novel positioning algorithm is introduced, utilizing both C-Taylor and adaptive robust Kalman filter, which is based on the Time of Arrival (TOA) method. This algorithm aims to address the limitations of Chan and Taylor algorithms and minimize the non-line-of-sight (NLOS) error. This algorithm has excellent theoretical research value and practical application value. © 2024 The Authors
引用
收藏
相关论文
共 50 条
  • [41] Indoor and Outdoor Precision Positioning System Based on Beidou Difference and UWB
    Hu, Siquan
    Xi, Zhiqiang
    She, Chundong
    [J]. 3RD ANNUAL INTERNATIONAL CONFERENCE ON INFORMATION SYSTEM AND ARTIFICIAL INTELLIGENCE (ISAI2018), 2018, 1069
  • [42] A UWB-Based Indoor Positioning System Employing Neural Networks
    Binghao Li
    Kai Zhao
    Eduardo Benitez Sandoval
    [J]. Journal of Geovisualization and Spatial Analysis, 2020, 4
  • [43] Localization terror Analysis of Indoor Positioning System Based on UWB Measurements
    Poulose, Alwin
    Eyobu, Odongo Steven
    Kim, Myeongjin
    Han, Dong Seog
    [J]. 2019 ELEVENTH INTERNATIONAL CONFERENCE ON UBIQUITOUS AND FUTURE NETWORKS (ICUFN 2019), 2019, : 84 - 88
  • [44] DS-UWB indoor positioning system implementation based on FPGAs
    Garcia, Enrique
    Poudereux, Pablo
    Hernandez, Alvaro
    Jesus Garcia, Juan
    Urena, Jesus
    [J]. SENSORS AND ACTUATORS A-PHYSICAL, 2013, 201 : 172 - 181
  • [45] A UWB-Based Indoor Positioning System Employing Neural Networks
    Li, Binghao
    Zhao, Kai
    Sandoval, Eduardo Benitez
    [J]. JOURNAL OF GEOVISUALIZATION AND SPATIAL ANALYSIS, 2020, 4 (02)
  • [46] The UWB based Forklift Trucks Indoor Positioning and Safety Management System
    Sun, Enji
    Ma, Ruixin
    [J]. 2017 IEEE 2ND ADVANCED INFORMATION TECHNOLOGY, ELECTRONIC AND AUTOMATION CONTROL CONFERENCE (IAEAC), 2017, : 86 - 90
  • [47] Network Scalability with Weight Analysis Based on UWB Indoor Positioning System
    Chen, Xiaosi
    Shen, Chong
    Gao, Qian
    Zhou, Qun
    Feng, Gaoang
    [J]. 2016 IEEE CONFERENCE ON WIRELESS SENSORS (ICWISE), 2016, : 95 - 99
  • [48] Design and Algorithm Research of Indoor Underwater Target Positioning System
    Zang Yunge
    Chen Xiyuan
    [J]. 2016 10TH INTERNATIONAL CONFERENCE ON SENSING TECHNOLOGY (ICST), 2016,
  • [49] Optical Indoor Positioning System Based on TFT Technology
    Gozse, Istvan
    [J]. SENSORS, 2016, 16 (01)
  • [50] The Research of Indoor Three-Dimensional Positioning Algorithm Based on Ultra-Wideband Technology
    Wang, Xin
    Huang, Zehua
    Zheng, FuQuan
    Tian, Xincheng
    [J]. PROCEEDINGS OF THE 39TH CHINESE CONTROL CONFERENCE, 2020, : 5144 - 5149