An Accurate Indoor User Position Estimator For Multiple Anchor UWB Localization
| Autor: | Odongo Steven Eyobu, Dong Seog Han, Alwin Poulose, Ziga Emersic |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
Computer science
Maximum likelihood Clock drift Estimator 02 engineering and technology 021001 nanoscience & nanotechnology Least squares Signal Extended Kalman filter Position (vector) 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing 0210 nano-technology Algorithm Multipath propagation |
| Zdroj: | ICTC |
| DOI: | 10.1109/ictc49870.2020.9289338 |
| Popis: | UWB-based positioning systems have been proven to provide a significant high level of ac-curacy hence offering a huge potential for a variety of indoor applications. However, the major challenges related to UWB localization are multipath effects, excess delay, clock drift, signal interferences and system computational time to estimate the user position. To compensate for these challenges, the UWB system uses multiple anchors in the experiment area and this gives accurate position results with minimum localization errors. However, the use of multiple anchors in the UWB system means processing large amounts of data in the system controller for localization, which leads to high computational time to estimate the current user position. To reduce the complexity of the UWB systems, we propose a position estimator for multiple anchor indoor localization, which uses the extended Kalman filter (EKF). The proposed UWB-EKF estimator was mathematically analysed and the simulation results were compared with classical localization algorithms considering the mean localization errors. In the simulation, three classical localization algorithms: linearized least square estimation (LLSE), weighted centroid estimation (WCE) and maximum likelihood estimation (MLE) were used for performance comparison. Thorough extensive simulation done in this study achieves results which demonstrate the effectiveness of the proposed UWB-EKF estimator for multiple anchor UWB indoor localization. |
| Databáze: | OpenAIRE |
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