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Enhancing Performance of Magnetic Field Based Indoor Localization Using Magnetic Patterns from Multiple Smartphones
Imran Ashraf1, Soojung Hur1, Yongwan Park1
1Department of Information and Communication Engineering, Yeungnam University, Gyeongbuk, Gyeongsan-si 38541, Korea.
Sensors (Basel, Switzerland)
|May 14, 2020
Summary
Indoor positioning using smartphones is challenging due to sensor variations. This study proposes a multi-smartphone geomagnetic database for consistent localization accuracy across devices, improving performance.
Area of Science:
- Computer Science
- Electrical Engineering
- Geophysics
Background:
- Global Positioning System (GPS) is inadequate for indoor environments.
- Smartphones offer sensors like magnetometers for indoor positioning.
- Existing geomagnetic localization methods suffer from device-specific sensor variations.
Purpose of the Study:
- To address the challenge of inconsistent indoor localization performance across different smartphones.
- To propose a novel approach for geomagnetic field-based indoor positioning.
- To improve the accuracy and reliability of smartphone-based localization.
Main Methods:
- Developed a geomagnetic field pattern (MP) database using data from multiple smartphones.
- Implemented a lightweight threshold technique to detect user motion using accelerometer data.
- Conducted experiments to evaluate localization performance across four different smartphone models.
Main Results:
- Localization performance was nearly identical across four different smartphones using the multi-smartphone database.
- The proposed method significantly improved localization consistency compared to single-smartphone databases.
- Overall smartphone localization performance showed marked improvement compared to previous research.
Conclusions:
- Utilizing a multi-smartphone geomagnetic database enhances the robustness and consistency of indoor localization.
- The proposed approach mitigates device-specific magnetic sensor variations.
- This method offers a promising solution for reliable location-based services on diverse smartphone hardware.
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