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

Yuan Xu; Yuriy S. Shmaliy; Choon Ki Ahn; Guohui Tian; Xiyuan Chen

doi:10.1049/iet-rsn.2017.0461

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

Yuan Xu, Yuriy S. Shmaliy, Choon Ki Ahn, Guohui Tian, Xiyuan Chen

Research output: Contribution to journal › Article › peer-review

54 Citations (Scopus)

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.

Original language	English
Pages (from-to)	750-756
Number of pages	7
Journal	IET Radar, Sonar and Navigation
Volume	12
Issue number	7
DOIs	https://doi.org/10.1049/iet-rsn.2017.0461
Publication status	Published - 2018 Jul 1

Bibliographical note

Funding Information:
This work was supported in part by the National Natural Science Foundation of China, under grant no. 61773239, in part by the China Postdoctoral Science Foundation, under grant no. 2017M622204

Publisher Copyright:
© The Institution of Engineering and Technology 2018.

ASJC Scopus subject areas

Electrical and Electronic Engineering

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10.1049/iet-rsn.2017.0461

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title = "Robust and accurate UWB-based indoor robot localisation using integrated EKF/EFIR filtering",

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.",

author = "Yuan Xu and Shmaliy, {Yuriy S.} and Ahn, {Choon Ki} and Guohui Tian and Xiyuan Chen",

note = "Funding Information: This work was supported in part by the National Natural Science Foundation of China, under grant no. 61773239, in part by the China Postdoctoral Science Foundation, under grant no. 2017M622204 Publisher Copyright: {\textcopyright} The Institution of Engineering and Technology 2018.",

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doi = "10.1049/iet-rsn.2017.0461",

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AU - Xu, Yuan

AU - Shmaliy, Yuriy S.

AU - Ahn, Choon Ki

AU - Tian, Guohui

AU - Chen, Xiyuan

N1 - Funding Information: This work was supported in part by the National Natural Science Foundation of China, under grant no. 61773239, in part by the China Postdoctoral Science Foundation, under grant no. 2017M622204 Publisher Copyright: © The Institution of Engineering and Technology 2018.

PY - 2018/7/1

Y1 - 2018/7/1

N2 - 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.

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

Abstract

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