| Autor: |
Chinyang Henry Tseng, Jiunn-Yih Wu |
| Jazyk: |
angličtina |
| Rok vydání: |
2024 |
| Předmět: |
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| Zdroj: |
Applied Bionics and Biomechanics, Vol 2024 (2024) |
| Druh dokumentu: |
article |
| ISSN: |
1754-2103 |
| DOI: |
10.1155/2024/1150076 |
| Popis: |
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. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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