Integration of GNSS and BLE Technology With Inertial Sensors for Real-Time Positioning in Urban Environments

被引:15
|
作者
Luo, Huan [1 ,2 ]
Li, Yaxin [1 ,2 ]
Wang, Jingxian [2 ]
Weng, Duojie [2 ]
Ye, Junhua [3 ]
Hsu, Li-Ta [4 ]
Chen, Wu [1 ,2 ]
机构
[1] Hong Kong Polytech Univ, Shenzhen Res Inst, Shenzhen, Peoples R China
[2] Hong Kong Polytech Univ, Dept Land Surveying & Geoinformat, Shenzhen, Peoples R China
[3] Changan Univ, Coll Geol Engn & Geomat, Xian 710054, Peoples R China
[4] Hong Kong Polytech Univ, Interdisciplinary Div Aeronaut & Aviat Engn, Hong Kong, Peoples R China
关键词
Global navigation satellite system; Inertial sensors; Urban areas; Estimation; Real-time systems; Sensor systems; Robustness; BLE; EKF; GNSS; heading estimation; PDR; positioning;
D O I
10.1109/ACCESS.2021.3052733
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The global navigation satellite system (GNSS) is widely used in smartphone positioning, but its performance can be degraded in urban environments because of signal reflections or blockages. To address these GNSS outages, pedestrian dead reckoning (PDR) is commonly used due to its significant improvements in both the stability and continuity of positioning, which are dependent on three key factors: continuous absolute position, heading and step information. Signals of opportunity are commonly used in positioning, whereas the installation of Bluetooth low energy (BLE) sensors on lampposts can provide an opportunity for positioning and heading estimation in urban canyons. In this article, a system integrating the GNSS, PDR, and BLE techniques is implemented in smartphones to provide a real-time positioning solution for pedestrians, which includes a new position correction method based on BLE heading, a reliable heading estimation integrating BLE and inertial sensors, an unconstrained step detection method with high accuracy, and an extended Kalman filter (EKF) to integrate multiple sensors and techniques. In several field experiments, with improvements in availability and robustness, the heading accuracy of the proposed fusion approach could reach approximately 3 degrees; the positioning accuracy achieved between 2.7 m and 4.2 m, compared with a 30 m error from the GNSS alone. Simultaneously, this system could achieve a high positioning accuracy of 2.4 m with unconstrained smartphones in a mixed environment. The proposed system has been demonstrated to perform well in urban canyons.
引用
收藏
页码:15744 / 15763
页数:20
相关论文
共 50 条
  • [1] Integration of Electronic Scanning Radars with Inertial Technology for Seamless Positioning in challenging GNSS Environments
    Rashed, Marwan A.
    Elhabiby, Mohamed
    Iqbal, Umar
    Korenberg, Michael J.
    Noureldin, Aboelmagd
    [J]. 2020 IEEE 92ND VEHICULAR TECHNOLOGY CONFERENCE (VTC2020-FALL), 2020,
  • [2] LiDAR Aided Cycle Slip Detection for GNSS Real-time Kinematic Positioning in Urban Environments
    Huang, Feng
    Wen, Weisong
    Ng, Hoi-Fung
    Hsu, Li-Ta
    [J]. 2022 IEEE 25TH INTERNATIONAL CONFERENCE ON INTELLIGENT TRANSPORTATION SYSTEMS (ITSC), 2022, : 1572 - 1578
  • [3] Developing a Novel Real-Time Indoor Positioning System Based on BLE Beacons and Smartphone Sensors
    Dinh, Thai-Mai Thi
    Duong, Ngoc-Son
    Nguyen, Quoc-Tuan
    [J]. IEEE SENSORS JOURNAL, 2021, 21 (20) : 23055 - 23068
  • [4] Real-Time Precise Positioning Method for Vehicle-Borne GNSS/MEMS IMU Integration in Urban Environment
    Zhu, Haoqi
    Wang, Fuhong
    Zhang, Wanwei
    Luan, Mengjie
    Cheng
    [J]. Wuhan Daxue Xuebao (Xinxi Kexue Ban)/Geomatics and Information Science of Wuhan University, 2023, 48 (07): : 1232 - 1240
  • [5] ACCURACY EVALUATION OF REAL-TIME GNSS PRECISION POSITIONING WITH RTX TRIMBLE TECHNOLOGY
    Ochalek, Agnieszka
    Niewiem, Witold
    Puniach, Edyta
    Cwiakala, Pawel
    [J]. CIVIL AND ENVIRONMENTAL ENGINEERING REPORTS, 2018, 28 (04) : 49 - 61
  • [6] A real-time combined quality control method for GNSS precise positioning in harsh environments
    Yuan, Haijun
    He, Xiufeng
    Zhang, Zhetao
    Liu, Huan
    Li, Yuan
    Jiang, Zixin
    [J]. ADVANCES IN SPACE RESEARCH, 2023, 71 (01) : 900 - 911
  • [7] R2-GVIO: A Robust, Real-Time GNSS-Visual-Inertial State Estimator in Urban Challenging Environments
    Song, Jiangbo
    Li, Wanqing
    Duan, Chufeng
    Zhu, Xiangwei
    [J]. IEEE INTERNET OF THINGS JOURNAL, 2024, 11 (12): : 22269 - 22282
  • [8] BAN TECHNOLOGY BASED WEARABLE WIRELESS SENSORS FOR REAL-TIME ENVIRONMENTS
    Kiran, Venneti
    Lenin, M.
    Thilagavathy, D. Archana
    [J]. ADVANCEMENTS IN AUTOMATION AND CONTROL TECHNOLOGIES, 2014, 573 : 381 - +
  • [9] Site-Specific Unmodeled Error Mitigation for GNSS Positioning in Urban Environments Using a Real-Time Adaptive Weighting Model
    Zhang, Zhetao
    Li, Bofeng
    Shen, Yunzhong
    Gao, Yang
    Wang, Miaomiao
    [J]. REMOTE SENSING, 2018, 10 (07)
  • [10] Full Real-Time Positioning and Attitude System Based on GNSS-RTK Technology
    Olivart i Llop, J. M.
    Moreno-Salinas, D.
    Sanchez, J.
    [J]. SUSTAINABILITY, 2020, 12 (23) : 1 - 21