Abstract
This paper proposes two schemes for indoor positioning by fusing Bluetooth beacons and a pedestrian dead reckoning (PDR) technique to provide meter-level positioning without additional infrastructure. As to the PDR approach, a more effective multi-threshold step detection algorithm is used to improve the positioning accuracy. According to pedestrians’ different walking patterns such as walking or running, this paper makes a comparative analysis of multiple step length calculation models to determine a linear computation model and the relevant parameters. In consideration of the deviation between the real heading and the value of the orientation sensor, a heading estimation method with real-time compensation is proposed, which is based on a Kalman filter with map geometry information. The corrected heading can inhibit the positioning error accumulation and improve the positioning accuracy of PDR. Moreover, this paper has implemented two positioning approaches integrated with Bluetooth and PDR. One is the PDR-based positioning method based on map matching and position correction through Bluetooth. There will not be too much calculation work or too high maintenance costs using this method. The other method is a fusion calculation method based on the pedestrians’ moving status (direct movement or making a turn) to determine adaptively the noise parameters in an Extended Kalman Filter (EKF) system. This method has worked very well in the elimination of various phenomena, including the “go and back” phenomenon caused by the instability of the Bluetooth-based positioning system and the “cross-wall” phenomenon due to the accumulative errors caused by the PDR algorithm. Experiments performed on the fourth floor of the School of Environmental Science and Spatial Informatics (SESSI) building in the China University of Mining and Technology (CUMT) campus showed that the proposed scheme can reliably achieve a 2-meter precision.
Highlights
Location Based Services (LBS) are mobile applications which rely on a user’s location to deliver context aware functionality
Solution III: This solution is named Bluetooth-based pedestrian dead reckoning (PDR), flagged as BEPDR, which is a PDR-based positioning method based on map matching with Bluetooth-based position correction
Based on the particular advantages of these two positioning systems using the Bluetooth Beacon and the PDR method, this paper proposes two fused positioning solutions following an improvement analysis of the corresponding gait detection, step length calculation and heading calculation through the PDR algorithm
Summary
Location Based Services (LBS) are mobile applications which rely on a user’s location to deliver context aware functionality. (1) Aiming at the indoor dead-reckoning positioning approach based on inertial technology, this paper proposes a peak-valley detection algorithm for multi-threshold step detection to identify the pedestrian gait. Through the research and analysis of the heading correction method, this paper proposes a heading estimation method with real-time compensation based on a Kalman filter according to the map geometry information to restrain the error accumulation, increasing the accuracy of heading calculation and improving the positioning accuracy of PDR algorithm. (2) Through the research and analysis of the positioning technology integrated with Bluetooth and PDR, this paper proposes two fusion models based on different principles separately through the following two methods: one has been integrated with PDR algorithm and the position correction through Bluetooth according to map matching and the other method is the adaptive noise extended.
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
