SHAKF-PU: Sage–Husa Adaptive Kalman Filtering-Based Pedestrian Characteristic Parameter Update Mechanism for Enhancing Step Length Estimation in Pedestrian Dead Reckoning
Step length estimation (SLE) is the core process for pedestrian dead reckoning (PDR) for indoor positioning. Original SLE requires accurate estimations of pedestrian characteristic parameter (PCP) by the linear update, which may cause large distance errors. To enhance SLE, this paper proposes the Sa...
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| Format: | Article |
| Language: | English |
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Wiley
2024-01-01
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| Series: | Applied Bionics and Biomechanics |
| Online Access: | http://dx.doi.org/10.1155/2024/1150076 |
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| author | Chinyang Henry Tseng Jiunn-Yih Wu |
| author_facet | Chinyang Henry Tseng Jiunn-Yih Wu |
| author_sort | Chinyang Henry Tseng |
| collection | DOAJ |
| description | Step length estimation (SLE) is the core process for pedestrian dead reckoning (PDR) for indoor positioning. Original SLE requires accurate estimations of pedestrian characteristic parameter (PCP) by the linear update, which may cause large distance errors. To enhance SLE, this paper proposes the Sage–Husa adaptive Kalman filtering-based PCP update (SHAKF-PU) mechanism for enhancing SLE in PDR. SHAKF has the characteristic of predicting the trend of historical data; the estimated PCP is closer to the true value than the linear update. Since different kinds of pedestrians can influence the PCP estimation, adaptive PCP estimation is required. Compared with the classical Kalman filter, SHAKF updates its Q and R parameters in each update period so the estimated PCP can be more accurate than other existing methods. The experimental results show that SHAKF-PU reduces the error by 24.86% compared to the linear update, and thus, the SHAKF-PU enhances the indoor positioning accuracy for PDR. |
| format | Article |
| id | doaj-art-4cbd97678cd049aa8f63623d574238e2 |
| institution | Kabale University |
| issn | 1754-2103 |
| language | English |
| publishDate | 2024-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Applied Bionics and Biomechanics |
| spelling | doaj-art-4cbd97678cd049aa8f63623d574238e22025-02-03T07:23:42ZengWileyApplied Bionics and Biomechanics1754-21032024-01-01202410.1155/2024/1150076SHAKF-PU: Sage–Husa Adaptive Kalman Filtering-Based Pedestrian Characteristic Parameter Update Mechanism for Enhancing Step Length Estimation in Pedestrian Dead ReckoningChinyang Henry Tseng0Jiunn-Yih Wu1Department of Computer Science and Information EngineeringCollege of MedicineStep length estimation (SLE) is the core process for pedestrian dead reckoning (PDR) for indoor positioning. Original SLE requires accurate estimations of pedestrian characteristic parameter (PCP) by the linear update, which may cause large distance errors. To enhance SLE, this paper proposes the Sage–Husa adaptive Kalman filtering-based PCP update (SHAKF-PU) mechanism for enhancing SLE in PDR. SHAKF has the characteristic of predicting the trend of historical data; the estimated PCP is closer to the true value than the linear update. Since different kinds of pedestrians can influence the PCP estimation, adaptive PCP estimation is required. Compared with the classical Kalman filter, SHAKF updates its Q and R parameters in each update period so the estimated PCP can be more accurate than other existing methods. The experimental results show that SHAKF-PU reduces the error by 24.86% compared to the linear update, and thus, the SHAKF-PU enhances the indoor positioning accuracy for PDR.http://dx.doi.org/10.1155/2024/1150076 |
| spellingShingle | Chinyang Henry Tseng Jiunn-Yih Wu SHAKF-PU: Sage–Husa Adaptive Kalman Filtering-Based Pedestrian Characteristic Parameter Update Mechanism for Enhancing Step Length Estimation in Pedestrian Dead Reckoning Applied Bionics and Biomechanics |
| title | SHAKF-PU: Sage–Husa Adaptive Kalman Filtering-Based Pedestrian Characteristic Parameter Update Mechanism for Enhancing Step Length Estimation in Pedestrian Dead Reckoning |
| title_full | SHAKF-PU: Sage–Husa Adaptive Kalman Filtering-Based Pedestrian Characteristic Parameter Update Mechanism for Enhancing Step Length Estimation in Pedestrian Dead Reckoning |
| title_fullStr | SHAKF-PU: Sage–Husa Adaptive Kalman Filtering-Based Pedestrian Characteristic Parameter Update Mechanism for Enhancing Step Length Estimation in Pedestrian Dead Reckoning |
| title_full_unstemmed | SHAKF-PU: Sage–Husa Adaptive Kalman Filtering-Based Pedestrian Characteristic Parameter Update Mechanism for Enhancing Step Length Estimation in Pedestrian Dead Reckoning |
| title_short | SHAKF-PU: Sage–Husa Adaptive Kalman Filtering-Based Pedestrian Characteristic Parameter Update Mechanism for Enhancing Step Length Estimation in Pedestrian Dead Reckoning |
| title_sort | shakf pu sage husa adaptive kalman filtering based pedestrian characteristic parameter update mechanism for enhancing step length estimation in pedestrian dead reckoning |
| url | http://dx.doi.org/10.1155/2024/1150076 |
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