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Sensors (Basel). 2019 Aug 9;19(16). pii: E3487. doi: 10.3390/s19163487.

A Robust Indoor Positioning Method based on Bluetooth Low Energy with Separate Channel Information.

Huang B1, Liu J1,2, Sun W3,4, Yang F5,6.

Author information

1
State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China.
2
Department of Remote Sensing and Photogrammetry and the Center of Excellence in Laser Scanning Research, Finnish Geospatial Research Institute, 02430 Masala, Finland.
3
Key Laboratory of Precise Engineering and Industry Surveying, National Administration of Surveying, Mapping and Geoinformation, Wuhan University, Wuhan 430079, China.
4
Wuhan Geomatics Institute, Wuhan 430079, China.
5
State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China. yangfanpost@whu.edu.cn.
6
State Key Laboratory of Geodesy and Earth's Geodynamics, Chinese Academy of Sciences, Wuhan 430079, China. yangfanpost@whu.edu.cn.

Abstract

Among the current indoor positioning technologies, Bluetooth low energy (BLE) has gained increasing attention. In particular, the traditional distance estimation derived from aggregate RSS and signal-attenuation models is generally unstable because of the complicated interference in indoor environments. To improve the adaptability and robustness of the BLE positioning system, we propose making full use of the three separate channels of BLE instead of their combination, which has generally been used before. In the first step, three signal-attenuation models are separately established for each BLE advertising channel in the offline phase, and a more stable distance in the online phase can be acquired by assembling measurements from all three channels with the distance decision strategy. Subsequently, a weighted trilateration method with uncertainties related to the distances derived in the first step is proposed to determine the user's optimal position. The test results demonstrate that our proposed algorithm for determining the distance error achieves a value of less than 2.2 m at 90%, while for the positioning error, it achieves a value of less than 2.4 m at 90%. Compared with the traditional methods, the positioning error of our method is reduced by 33% to 38% for different smartphones and scenarios.

KEYWORDS:

Bluetooth low energy (BLE); distance decision strategy; indoor positioning; separate channels; separate signal-attenuation models; weighted trilateration

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