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An Adaptive Bluetooth/Wi-Fi Fingerprint Positioning Method based on Gaussian Process Regression and Relative
Hongji Cao1,2, Yunjia Wang3,4, Jingxue Bi5
1Key Laboratory of Land Environment and Disaster Monitoring, MNR, China University of Mining and Technology, Xuzhou 221116, China. hjcao@cumt.edu.cn.
This study introduces an adaptive method fusing Bluetooth and Wi-Fi positioning by using Gaussian process regression and relative distance. The novel approach enhances positioning accuracy, achieving a mean error of 2.06 m.
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Area of Science:
- Indoor positioning systems
- Wireless sensor networks
- Signal processing
Background:
- Accurate indoor positioning is crucial for various applications.
- Fusion of Bluetooth fingerprint positioning (BFP) and Wi-Fi fingerprint positioning (WFP) requires trusted data.
- Existing methods struggle with integrating heterogeneous positioning data effectively.
Purpose of the Study:
- To propose an adaptive method for fusing BFP and WFP using Gaussian process regression (GPR) and relative distance (RD).
- To develop a system that can select trusted positioning results for fusion, improving overall accuracy.
- To enhance the reliability and precision of indoor positioning systems.
Main Methods:
- Construction of Bluetooth and Wi-Fi fingerprint databases using received signal strength (RSS) measurements.
- Building fingerprint positioning error prediction models with GPR.
- Online determination of trusted positioning results using RD and prediction models.
- Fusion strategy: selecting a single trusted result or the mean of both if equally trusted/untrusted.
Main Results:
- The proposed adaptive method achieved a mean positioning error of 2.06 m.
- A root-mean-square error (RMSE) of 1.449 m was recorded.
- The method demonstrated superior performance compared to standalone BFP and WFP.
Conclusions:
- The adaptive GPR and RD-based method effectively fuses BFP and WFP by selecting trusted positioning results.
- This approach significantly improves indoor positioning accuracy and reliability.
- The proposed method offers a robust solution for integrated wireless positioning systems.

