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Robust and accurate UWB-based indoor robot localisation using integrated EKF/EFIR filtering

Authors
Xu, YuanShmaliy, Yuriy S.Ahn, Choon KiTian, GuohuiChen, Xiyuan
Issue Date
7월-2018
Publisher
INST ENGINEERING TECHNOLOGY-IET
Keywords
nonlinear filters; FIR filters; Kalman filters; mobile robots; UWB-range robot localisation; indoor robot localisation; integrated EKF; EFIR filtering; extended Kalman filter; extended unbiased finite impulse response filter; ultrawideband-based scheme; probabilistic weights; uncertain noise environments
Citation
IET RADAR SONAR AND NAVIGATION, v.12, no.7, pp.750 - 756
Indexed
SCIE
SCOPUS
Journal Title
IET RADAR SONAR AND NAVIGATION
Volume
12
Number
7
Start Page
750
End Page
756
URI
https://scholar.korea.ac.kr/handle/2021.sw.korea/74487
DOI
10.1049/iet-rsn.2017.0461
ISSN
1751-8784
Abstract
A novel ultra wideband (UWB)-based scheme is proposed to provide robust and accurate robot localisation in indoor environments. An extended Kalman filter (EKF), which is suboptimal, is combined in the main estimator design with an extended unbiased finite impulse response (EFIR) filter, which has better robustness. In the integrated EKF/EFIR algorithm, the EFIR filter and the EKF operate in parallel and the final estimate is obtained by fusing the outputs of both filters using probabilistic weights. Accordingly, the EKF/EFIR filter output ranges close to the most accurate one of the EKF and EFIR filters. Experimental testing has shown that the EKF/EFIR-based UWB-range robot localisation is more robust than the EKF- and EFIR-based ones in uncertain noise environments.
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공과대학 (전기전자공학부)
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