Integrity Monitoring for Bluetooth Low Energy Beacons RSSI Based Indoor Positioning

IEEE Access

Hongji Yan¹  Xinlian Liang²  Haiyun Yao³  Hong Shu³  Hongxing Sun³ 

[1] Application Integration Development Department of Integration and Maintenance Department, Huawei Technology Co., Ltd., Wuhan, China;Department of Remote Sensing and Photogrammetry, Finnish Geospatial Research Institute, Masala, Finland;State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan, China;

关键词: Indoor positioning;    integrity monitoring;    least square;    parity vector;    maximum likelihood estimation;    BLE beacons;   

DOI  :  10.1109/ACCESS.2020.3038894

来源: DOAJ

【 摘 要 】

Indoor wireless positioning using Bluetooth Low Energy (BLE) beacons have attracted considerable attention from industry and academia given the many advantages of this technology such as low power consumption, low cost, easy layout, high availability, and high precision. However, the indoor positioning accuracy always suffers from non-line of sight (NLOS) propagation, stemming from the frequently occurring instances of reflection, refraction, or scattering of BLE radio signals due to the complexity of indoor environments. This article proposes an integrity monitoring (IM) algorithm to detect and eliminate two gross errors simultaneously to solve the adverse effects caused by the NLOS. The logarithmic attenuation model based on the received signal strength indication (RSSI) of BLE realizes positioning by combining trilateration and Least Squares Based on the Taylor expansion (LSBT). Furthermore, the IM based on hypothesis testing is employed to improve the positioning quality andthe users will be alerted in time to avoid risk from positioning accuracy no longer meet user's requirement. The performance of the proposed IM algorithm has been extensively tested by conducting simulation and field experiments. The experimental results show that the IM algorithm significantly improved BLE positioning accuracy as well as the robustness of the positioning system. The 90% average error (1.9143m) in seven groups of single point experiments was reduced by 34.48% over the 90% average error (2.9143m) of the LSBT method after performing IM, and the maximum error during continuous positioning did not exceed 3m after performing IM, which were better than only using LSBT positioning.

【 授权许可】

Unknown