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 journalArticle

8 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 languageEnglish
Pages (from-to)750-756
Number of pages7
JournalIET Radar, Sonar and Navigation
Volume12
Issue number7
DOIs
Publication statusPublished - 2018 Jul 1

ASJC Scopus subject areas

  • Electrical and Electronic Engineering

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