An Efficient IAKF Approach for Indoor Positioning Drift Correction
In this study, an indoor positioning shift correction architecture was developed with an improved adaptive Kalman filter (IAKF) algorithm for the people interference condition. Indoor positioning systems (IPSs) use ultra-wideband (UWB) communication technology. Triangulation positioning algorithms a...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-07-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/22/15/5697 |
| _version_ | 1797440687589818368 |
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| author | Shang-Hsien Lin Hung-Hsien Chang Chien Wei-Wen Wang Kuang-Hao Lin Guan-Jin Li |
| author_facet | Shang-Hsien Lin Hung-Hsien Chang Chien Wei-Wen Wang Kuang-Hao Lin Guan-Jin Li |
| author_sort | Shang-Hsien Lin |
| collection | DOAJ |
| description | In this study, an indoor positioning shift correction architecture was developed with an improved adaptive Kalman filter (IAKF) algorithm for the people interference condition. Indoor positioning systems (IPSs) use ultra-wideband (UWB) communication technology. Triangulation positioning algorithms are generally employed for determining the position of a target. However, environmental communication factors and different network topologies produce localization drift errors in IPSs. Therefore, the drift error of real-time positioning points under various environmental factors and the correction of the localization drift error are discussed. For localization drift error, four algorithms were simulated and analyzed: movement average (MA), least square (LS), Kalman filter (KF), and IAKF. Finally, the IAKF algorithm was implemented and verified on the UWB indoor positioning system. The measurement results showed that the drift errors improved by 60% and 74.15% in environments with and without surrounding crowds, respectively. Thus, the coordinates of real-time positioning points are closer to those of actual targets. |
| first_indexed | 2024-03-09T12:11:55Z |
| format | Article |
| id | doaj.art-935d2ccc070d48f58747bb4cc2dc099c |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-09T12:11:55Z |
| publishDate | 2022-07-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-935d2ccc070d48f58747bb4cc2dc099c2023-11-30T22:51:22ZengMDPI AGSensors1424-82202022-07-012215569710.3390/s22155697An Efficient IAKF Approach for Indoor Positioning Drift CorrectionShang-Hsien Lin0Hung-Hsien Chang Chien1Wei-Wen Wang2Kuang-Hao Lin3Guan-Jin Li4Systems Development Center, National Chung-Shan Institute of Science and Technology, Taoyuan 325, TaiwanSystems Development Center, National Chung-Shan Institute of Science and Technology, Taoyuan 325, TaiwanSystems Development Center, National Chung-Shan Institute of Science and Technology, Taoyuan 325, TaiwanDepartment of Electrical Engineering, National Formosa University, Yunlin 632, TaiwanDepartment of Electrical Engineering, National Formosa University, Yunlin 632, TaiwanIn this study, an indoor positioning shift correction architecture was developed with an improved adaptive Kalman filter (IAKF) algorithm for the people interference condition. Indoor positioning systems (IPSs) use ultra-wideband (UWB) communication technology. Triangulation positioning algorithms are generally employed for determining the position of a target. However, environmental communication factors and different network topologies produce localization drift errors in IPSs. Therefore, the drift error of real-time positioning points under various environmental factors and the correction of the localization drift error are discussed. For localization drift error, four algorithms were simulated and analyzed: movement average (MA), least square (LS), Kalman filter (KF), and IAKF. Finally, the IAKF algorithm was implemented and verified on the UWB indoor positioning system. The measurement results showed that the drift errors improved by 60% and 74.15% in environments with and without surrounding crowds, respectively. Thus, the coordinates of real-time positioning points are closer to those of actual targets.https://www.mdpi.com/1424-8220/22/15/5697indoor positioning systemultra-widebandKalman filterRSSIAoA |
| spellingShingle | Shang-Hsien Lin Hung-Hsien Chang Chien Wei-Wen Wang Kuang-Hao Lin Guan-Jin Li An Efficient IAKF Approach for Indoor Positioning Drift Correction Sensors indoor positioning system ultra-wideband Kalman filter RSSI AoA |
| title | An Efficient IAKF Approach for Indoor Positioning Drift Correction |
| title_full | An Efficient IAKF Approach for Indoor Positioning Drift Correction |
| title_fullStr | An Efficient IAKF Approach for Indoor Positioning Drift Correction |
| title_full_unstemmed | An Efficient IAKF Approach for Indoor Positioning Drift Correction |
| title_short | An Efficient IAKF Approach for Indoor Positioning Drift Correction |
| title_sort | efficient iakf approach for indoor positioning drift correction |
| topic | indoor positioning system ultra-wideband Kalman filter RSSI AoA |
| url | https://www.mdpi.com/1424-8220/22/15/5697 |
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