Dynamic Accuracy Estimation in a Wi-Fi-based Positioning System
Fuente:
arXiv
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| Autori principali: | , |
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| Natura: | Preprint |
| Pubblicazione: |
2026
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| _version_ | 1866909980241690624 |
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| author | Kolakowski, Marcin Djaja-Josko, Vitomir |
| author_facet | Kolakowski, Marcin Djaja-Josko, Vitomir |
| contents | The paper presents a concept of a dynamic accuracy estimation method, in which the localization errors are derived based on the measurement results used by the positioning algorithm. The concept was verified experimentally in a Wi\nobreakdash-Fi based indoor positioning system, where several regression methods were tested (linear regression, random forest, k-nearest neighbors, and neural networks). The highest positioning error estimation accuracy was achieved for random forest regression, with a mean absolute error of 0.72 m. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2601_00999 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Dynamic Accuracy Estimation in a Wi-Fi-based Positioning System Kolakowski, Marcin Djaja-Josko, Vitomir Signal Processing Machine Learning The paper presents a concept of a dynamic accuracy estimation method, in which the localization errors are derived based on the measurement results used by the positioning algorithm. The concept was verified experimentally in a Wi\nobreakdash-Fi based indoor positioning system, where several regression methods were tested (linear regression, random forest, k-nearest neighbors, and neural networks). The highest positioning error estimation accuracy was achieved for random forest regression, with a mean absolute error of 0.72 m. |
| title | Dynamic Accuracy Estimation in a Wi-Fi-based Positioning System |
| topic | Signal Processing Machine Learning |
| url | https://arxiv.org/abs/2601.00999 |