A self-learning mean optimization filter to improve bluetooth 5.1 AoA indoor positioning accuracy for ship environments
As COVID-19 is still spreading globally, the narrow ship space makes COVID-19 easier for the virus to infect ship passengers. Tracking close contacts remains an effective way to reduce the risk of virus transmission. Therefore, indoor positioning technology should be developed for ship environments....
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| Format: | Article |
| Language: | English |
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Elsevier
2023-03-01
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| Series: | Journal of King Saud University: Computer and Information Sciences |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S1319157823000277 |
| _version_ | 1797894672079650816 |
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| author | Qianfeng Lin Jooyoung Son Hyeongseol Shin |
| author_facet | Qianfeng Lin Jooyoung Son Hyeongseol Shin |
| author_sort | Qianfeng Lin |
| collection | DOAJ |
| description | As COVID-19 is still spreading globally, the narrow ship space makes COVID-19 easier for the virus to infect ship passengers. Tracking close contacts remains an effective way to reduce the risk of virus transmission. Therefore, indoor positioning technology should be developed for ship environments. Today, almost all smart devices are equipped with Bluetooth. The Angle of Arrival (AoA) using Bluetooth 5.1 indoor positioning technology is well suited for ship environments. But the narrow ship space and steel walls make the multipath effect more pronounced in ship environments. This also means that more noises are included in the signal. In the Uniform Rectangular Array (URA) type receiving antenna array, elevation and azimuth angles are two important parameters for the AoA indoor positioning technology. Elevation and azimuth angles are unstable because of the influence of noise. In this paper, a Self-Learning Mean Optimization Filter (SLMOF) is proposed. The goal of SLMOF is to find the optimal elevation and azimuth angles as a way to improve the Bluetooth 5.1 AoA indoor positioning accuracy. The experimental results show that the Root Mean Square Error (RMSE) of SLMOF is 0.44 m, which improves the accuracy by 72% compared to Kalman Filter (KF). This method can be applied to find the optimal average in every dataset. |
| first_indexed | 2024-04-10T07:14:10Z |
| format | Article |
| id | doaj.art-845d9639490143f2b8d531e901cbba11 |
| institution | Directory Open Access Journal |
| issn | 1319-1578 |
| language | English |
| last_indexed | 2024-04-10T07:14:10Z |
| publishDate | 2023-03-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Journal of King Saud University: Computer and Information Sciences |
| spelling | doaj.art-845d9639490143f2b8d531e901cbba112023-02-26T04:26:50ZengElsevierJournal of King Saud University: Computer and Information Sciences1319-15782023-03-013535973A self-learning mean optimization filter to improve bluetooth 5.1 AoA indoor positioning accuracy for ship environmentsQianfeng Lin0Jooyoung Son1Hyeongseol Shin2Department of Computer Engineering, Korea Maritime and Ocean University, 727 Taejong-ro, Yeongdo-Gu, Busan 49112, South KoreaDivision of Marine IT Engineering, Korea Maritime and Ocean University, 727 Taejong-ro, Yeongdo-Gu, Busan 49112, South Korea; Corresponding author at: Division of Marine IT Engineering, Korea Maritime and Ocean University, 727 Taejong-ro, Yeongdo-Gu, Busan 49112, South Korea.Division of Marine System Engineering, Korea Maritime and Ocean University, 727 Taejong-ro, Yeongdo-Gu, Busan 49112, South KoreaAs COVID-19 is still spreading globally, the narrow ship space makes COVID-19 easier for the virus to infect ship passengers. Tracking close contacts remains an effective way to reduce the risk of virus transmission. Therefore, indoor positioning technology should be developed for ship environments. Today, almost all smart devices are equipped with Bluetooth. The Angle of Arrival (AoA) using Bluetooth 5.1 indoor positioning technology is well suited for ship environments. But the narrow ship space and steel walls make the multipath effect more pronounced in ship environments. This also means that more noises are included in the signal. In the Uniform Rectangular Array (URA) type receiving antenna array, elevation and azimuth angles are two important parameters for the AoA indoor positioning technology. Elevation and azimuth angles are unstable because of the influence of noise. In this paper, a Self-Learning Mean Optimization Filter (SLMOF) is proposed. The goal of SLMOF is to find the optimal elevation and azimuth angles as a way to improve the Bluetooth 5.1 AoA indoor positioning accuracy. The experimental results show that the Root Mean Square Error (RMSE) of SLMOF is 0.44 m, which improves the accuracy by 72% compared to Kalman Filter (KF). This method can be applied to find the optimal average in every dataset.http://www.sciencedirect.com/science/article/pii/S1319157823000277Angle of arrivalBluetoothIndoor positioningShip environments |
| spellingShingle | Qianfeng Lin Jooyoung Son Hyeongseol Shin A self-learning mean optimization filter to improve bluetooth 5.1 AoA indoor positioning accuracy for ship environments Journal of King Saud University: Computer and Information Sciences Angle of arrival Bluetooth Indoor positioning Ship environments |
| title | A self-learning mean optimization filter to improve bluetooth 5.1 AoA indoor positioning accuracy for ship environments |
| title_full | A self-learning mean optimization filter to improve bluetooth 5.1 AoA indoor positioning accuracy for ship environments |
| title_fullStr | A self-learning mean optimization filter to improve bluetooth 5.1 AoA indoor positioning accuracy for ship environments |
| title_full_unstemmed | A self-learning mean optimization filter to improve bluetooth 5.1 AoA indoor positioning accuracy for ship environments |
| title_short | A self-learning mean optimization filter to improve bluetooth 5.1 AoA indoor positioning accuracy for ship environments |
| title_sort | self learning mean optimization filter to improve bluetooth 5 1 aoa indoor positioning accuracy for ship environments |
| topic | Angle of arrival Bluetooth Indoor positioning Ship environments |
| url | http://www.sciencedirect.com/science/article/pii/S1319157823000277 |
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