TY - JOUR
T1 - Integration of GNSS and BLE Technology with Inertial Sensors for Real-time Positioning in Urban Environments
AU - Luo, Huan
AU - Li, Yaxin
AU - Wang, Jingxian
AU - Weng, Duojie
AU - Ye, Junhua
AU - Hsu, Li Ta
AU - Chen, Wu
N1 - Funding Information:
The research was substantially funded by the Shenzhen Science and Technology Innovation Commission (Project No. JCYJ20170818104822282), Hong Kong Research Grants Council (RGC) Competitive Earmarked Research Grant (Project No: 152223/18E), and the research fund from the Research Institute of Sustainable Urban Development, The Hong Kong Polytechnic University.
Publisher Copyright:
© 2013 IEEE.
PY - 2021/1/19
Y1 - 2021/1/19
N2 - 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.
AB - 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.
KW - BLE
KW - EKF
KW - GNSS
KW - PDR
KW - heading estimation
KW - positioning
UR - http://www.scopus.com/inward/record.url?scp=85099725842&partnerID=8YFLogxK
U2 - 10.1109/ACCESS.2021.3052733
DO - 10.1109/ACCESS.2021.3052733
M3 - Journal article
AN - SCOPUS:85099725842
SN - 2169-3536
VL - 9
SP - 15744
EP - 15763
JO - IEEE Access
JF - IEEE Access
M1 - 9328421
ER -