UWB Indoor Positioning with Kalman Filters
Mäkipää, Antti-Jussi (2023)
Mäkipää, Antti-Jussi
2023
Sähkötekniikan DI-ohjelma - Master's Programme in Electrical Engineering
Informaatioteknologian ja viestinnän tiedekunta - Faculty of Information Technology and Communication Sciences
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Hyväksymispäivämäärä
2023-11-16
Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:tuni-202311109572
https://urn.fi/URN:NBN:fi:tuni-202311109572
Tiivistelmä
This thesis explores the application of Kalman Filters to Ultra-Wideband (UWB) indoor positioning systems (IPS), addressed through two primary research questions: "How can Kalman Filters be used in UWB indoor positioning?" and "How do different Kalman Filter implementations perform in the specific indoor positioning setup of this study?". The first question is explored through an extensive literature review, while the latter is addressed via practical experimentation in Veracell’s office environment.
The literature review is bifurcated, focusing on the theoretical underpinnings of UWB and the practical application of Kalman Filters for indoor positioning. Insights into the characteristics of UWB, various UWB ranging methods, the foundational principles of Kalman Filters, and two specific types - Extended Kalman Filter (EKF) and Unscented Kalman Filter (UKF) - are elaborated. This review serves as a precursor to the empirical component of the thesis, aiming to identify and evaluate an alternative positioning methodology against Veracell’s existing system.
The second research question is addressed through the collection of two distinct datasets from Veracell’s indoor positioning environment and the implementation of EKF and UKF algorithms for positioning analysis. Experimentation results suggest that the integration of Kalman Filters enhances the accuracy of the UWB indoor positioning system.
While these findings are promising, additional research and empirical testing are requisite to validate the adaptability and efficacy of Kalman Filters across diverse indoor positioning contexts, ensuring their optimized performance in Veracell’s and analogous IPS implementations.
The literature review is bifurcated, focusing on the theoretical underpinnings of UWB and the practical application of Kalman Filters for indoor positioning. Insights into the characteristics of UWB, various UWB ranging methods, the foundational principles of Kalman Filters, and two specific types - Extended Kalman Filter (EKF) and Unscented Kalman Filter (UKF) - are elaborated. This review serves as a precursor to the empirical component of the thesis, aiming to identify and evaluate an alternative positioning methodology against Veracell’s existing system.
The second research question is addressed through the collection of two distinct datasets from Veracell’s indoor positioning environment and the implementation of EKF and UKF algorithms for positioning analysis. Experimentation results suggest that the integration of Kalman Filters enhances the accuracy of the UWB indoor positioning system.
While these findings are promising, additional research and empirical testing are requisite to validate the adaptability and efficacy of Kalman Filters across diverse indoor positioning contexts, ensuring their optimized performance in Veracell’s and analogous IPS implementations.