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A Performance Improvement for Indoor Positioning Systems Using Earth’s Magnetic Field

Although most indoor positioning systems use radio waves, such as Wi-Fi, Bluetooth, or RFID, for application in department stores, exhibition halls, stations, and airports, the accuracy of such technology is easily affected by human shadowing and multipath propagation delay. This study combines the...

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Autores principales: Yeh, Sheng-Cheng, Chiu, Hsien-Chieh, Kao, Chih-Yang, Wang, Chia-Hui
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10457947/
https://www.ncbi.nlm.nih.gov/pubmed/37631643
http://dx.doi.org/10.3390/s23167108
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author Yeh, Sheng-Cheng
Chiu, Hsien-Chieh
Kao, Chih-Yang
Wang, Chia-Hui
author_facet Yeh, Sheng-Cheng
Chiu, Hsien-Chieh
Kao, Chih-Yang
Wang, Chia-Hui
author_sort Yeh, Sheng-Cheng
collection PubMed
description Although most indoor positioning systems use radio waves, such as Wi-Fi, Bluetooth, or RFID, for application in department stores, exhibition halls, stations, and airports, the accuracy of such technology is easily affected by human shadowing and multipath propagation delay. This study combines the earth’s magnetic field strength and Wi-Fi signals to obtain the indoor positioning information with high availability. Wi-Fi signals are first used to identify the user’s area under several kinds of environment partitioning methods. Then, the signal pattern comparison is used for positioning calculations using the strength change in the earth’s magnetic field among the east–west, north–south, and vertical directions at indoor area. Finally, the k-nearest neighbors (KNN) method and fingerprinting algorithm are used to calculate the fine-grained indoor positioning information. The experiment results show that the average positioning error is 0.57 m in 12-area partitioning, which is almost a 90% improvement in relation to that of one area partitioning. This study also considers the positioning error if the device is held at different angles by hand. A rotation matrix is used to convert the magnetic sensor coordinates from a mobile phone related coordinates into the geographic coordinates. The average positioning error is decreased by 68%, compared to the original coordinates in 12-area partitioning with a 30-degree pitch. In the offline procedure, only the northern direction data are used, which is reduced by 75%, to give an average positioning error of 1.38 m. If the number of reference points is collected every 2 m for reducing 50% of the database requirement, the average positioning error is 1.77 m.
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spelling pubmed-104579472023-08-27 A Performance Improvement for Indoor Positioning Systems Using Earth’s Magnetic Field Yeh, Sheng-Cheng Chiu, Hsien-Chieh Kao, Chih-Yang Wang, Chia-Hui Sensors (Basel) Article Although most indoor positioning systems use radio waves, such as Wi-Fi, Bluetooth, or RFID, for application in department stores, exhibition halls, stations, and airports, the accuracy of such technology is easily affected by human shadowing and multipath propagation delay. This study combines the earth’s magnetic field strength and Wi-Fi signals to obtain the indoor positioning information with high availability. Wi-Fi signals are first used to identify the user’s area under several kinds of environment partitioning methods. Then, the signal pattern comparison is used for positioning calculations using the strength change in the earth’s magnetic field among the east–west, north–south, and vertical directions at indoor area. Finally, the k-nearest neighbors (KNN) method and fingerprinting algorithm are used to calculate the fine-grained indoor positioning information. The experiment results show that the average positioning error is 0.57 m in 12-area partitioning, which is almost a 90% improvement in relation to that of one area partitioning. This study also considers the positioning error if the device is held at different angles by hand. A rotation matrix is used to convert the magnetic sensor coordinates from a mobile phone related coordinates into the geographic coordinates. The average positioning error is decreased by 68%, compared to the original coordinates in 12-area partitioning with a 30-degree pitch. In the offline procedure, only the northern direction data are used, which is reduced by 75%, to give an average positioning error of 1.38 m. If the number of reference points is collected every 2 m for reducing 50% of the database requirement, the average positioning error is 1.77 m. MDPI 2023-08-11 /pmc/articles/PMC10457947/ /pubmed/37631643 http://dx.doi.org/10.3390/s23167108 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Yeh, Sheng-Cheng
Chiu, Hsien-Chieh
Kao, Chih-Yang
Wang, Chia-Hui
A Performance Improvement for Indoor Positioning Systems Using Earth’s Magnetic Field
title A Performance Improvement for Indoor Positioning Systems Using Earth’s Magnetic Field
title_full A Performance Improvement for Indoor Positioning Systems Using Earth’s Magnetic Field
title_fullStr A Performance Improvement for Indoor Positioning Systems Using Earth’s Magnetic Field
title_full_unstemmed A Performance Improvement for Indoor Positioning Systems Using Earth’s Magnetic Field
title_short A Performance Improvement for Indoor Positioning Systems Using Earth’s Magnetic Field
title_sort performance improvement for indoor positioning systems using earth’s magnetic field
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10457947/
https://www.ncbi.nlm.nih.gov/pubmed/37631643
http://dx.doi.org/10.3390/s23167108
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