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EKF-based and Geometry-based Positioning under Location Uncertainty of Access Nodes in Indoor Environment

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Details

Original languageEnglish
Title of host publication2019 International Conference on Indoor Positioning and Indoor Navigation (IPIN)
PublisherIEEE
Number of pages7
ISBN (Electronic)978-1-7281-1788-1
ISBN (Print)978-1-7281-1789-8
DOIs
Publication statusPublished - 30 Sep 2019
Publication typeA4 Article in a conference publication
EventInternational Conference on Indoor Positioning and Indoor Navigation -
Duration: 1 Jan 1900 → …

Publication series

NameInternational Conference on Indoor Positioning and Indoor Navigation
ISSN (Print)2162-7347
ISSN (Electronic)2471-917X

Conference

ConferenceInternational Conference on Indoor Positioning and Indoor Navigation
Period1/01/00 → …

Abstract

High accuracy positioning enabled by 5G cellular networks will play a crucial role in the robot-based industrial applications, where the vertical accuracy will be as significant as the 3D accuracy. Aiming at target applications relying on flying robots in industrial environments, this paper presents and formulates two positioning algorithms when the location uncertainty of the access nodes (ANs) is taken into consideration. The first algorithm is a low-complexity geometry-based 3D positioning algorithm that utilizes both time-of-arrival and angle-of-arrival measurements. The second algorithm relies on extended Kalman Filter (EKF)-based positioning, by mapping the ANs' location uncertainty into the measurement noise statistics. The performance of the two proposed method is studied in terms of 3D and vertical positioning accuracy, sensitivity to location uncertainty of the ANs, and computational complexity in indoor scenarios. Based on the conducted complexity analysis, the proposed geometry-based algorithm is computationally more efficient than the EKF-based algorithm. In addition, the proposed geometry-based positioning method demonstrates a higher robustness against a high location uncertainty of ANs than the considered EKF-based method.

Keywords

  • robot tracking, 5G networks, indoor positioning, non-linear mapping, location uncertainty of access nodes

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