UWB-Based NLOS Identification and Mitigation: A Performance Evaluation in Dynamic Settings

Raphael E. Nkrow; Bruno J. Silva; Dutliff Boshoff; Gerhard P. Hancke

doi:10.1109/IECON51785.2023.10311874

UWB-Based NLOS Identification and Mitigation: A Performance Evaluation in Dynamic Settings

Department of Computer Science

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

11 Citations (Scopus)

43 Downloads (CityUHK Scholars)

Abstract

In the fourth industrial revolution (Industry 4.0), robotics and autonomous navigational systems are essential for smart agriculture. Industrial smart agriculture relies heavily on autonomous navigational systems, which have important uses in unmanned farms, industrial supply chains, etc. For effective navigation of autonomous robotic systems in industrial settings, indoor-based positioning and navigation technologies play key roles. However, positioning performance is severely impacted by the abundance of Non-Line-Of-Sight (NLOS) components due to the dynamic nature of industrial environments. Different approaches have been proposed in literature for identifying and mitigating NLOS components in UWB positioning systems. However, the performance of these proposed approaches on par in multiple distinct environments is unknown. In this paper, we experimentally investigate and compare the performance of recent UWB-based state-of-the-art approaches to NLOS identification and mitigation on par, in distinct and dynamic obstructed settings to ascertain two key insights: i) how the performance of existing approaches change based on the environment type; ii) the impact of the environment type on NLOS identification and mitigation. © 2023 IEEE.

Original language	English
Title of host publication	IECON 2023 - 49th Annual Conference of the IEEE Industrial Electronics Society
Publisher	IEEE
Number of pages	6
ISBN (Electronic)	9798350331820
ISBN (Print)	979-8-3503-3183-7
DOIs	https://doi.org/10.1109/IECON51785.2023.10311874
Publication status	Published - 2023
Event	49th Annual Conference of the IEEE Industrial Electronics Society (IECON 2023) - Marina Bay Sands Expo and Convention Centre, Singapore Duration: 16 Oct 2023 → 19 Oct 2023 https://www.iecon2023.org/

Publication series

Name	IECON Proceedings (Industrial Electronics Conference)
ISSN (Print)	2162-4704
ISSN (Electronic)	2577-1647

Conference

Conference	49th Annual Conference of the IEEE Industrial Electronics Society (IECON 2023)
Abbreviated title	IEEE IECON 2023
Place	Singapore
Period	16/10/23 → 19/10/23
Internet address	https://www.iecon2023.org/

Funding

This work was supported by the Research Grants Council of Hong Kong under project CityU 11208122.

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 9 Industry, Innovation, and Infrastructure

Research Keywords

Localization
NLOS
Ranging
Time-of-Flight

Publisher's Copyright Statement

COPYRIGHT TERMS OF DEPOSITED POSTPRINT FILE: © 2023 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. Nkrow, R. E., Silva, B. J., Boshoff, D., & Hancke, G. P. (2023). UWB-Based NLOS Identification and Mitigation: A Performance Evaluation in Dynamic Settings. In IECON 2023 - 49th Annual Conference of the IEEE Industrial Electronics Society (IECON Proceedings (Industrial Electronics Conference)). Institute of Electrical and Electronics Engineers, Inc. https://doi.org/10.1109/IECON51785.2023.10311874

RGC Funding Information

RGC-funded

Access Output

10.1109/IECON51785.2023.10311874

180170954.pdfPost-print, 527 KB

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Cite this

@inproceedings{f8828ce782b7451a99a1bd0972d15f8a,

title = "UWB-Based NLOS Identification and Mitigation: A Performance Evaluation in Dynamic Settings",

abstract = "In the fourth industrial revolution (Industry 4.0), robotics and autonomous navigational systems are essential for smart agriculture. Industrial smart agriculture relies heavily on autonomous navigational systems, which have important uses in unmanned farms, industrial supply chains, etc. For effective navigation of autonomous robotic systems in industrial settings, indoor-based positioning and navigation technologies play key roles. However, positioning performance is severely impacted by the abundance of Non-Line-Of-Sight (NLOS) components due to the dynamic nature of industrial environments. Different approaches have been proposed in literature for identifying and mitigating NLOS components in UWB positioning systems. However, the performance of these proposed approaches on par in multiple distinct environments is unknown. In this paper, we experimentally investigate and compare the performance of recent UWB-based state-of-the-art approaches to NLOS identification and mitigation on par, in distinct and dynamic obstructed settings to ascertain two key insights: i) how the performance of existing approaches change based on the environment type; ii) the impact of the environment type on NLOS identification and mitigation. {\textcopyright} 2023 IEEE.",

keywords = "Localization, NLOS, Ranging, Time-of-Flight",

author = "Nkrow, \{Raphael E.\} and Silva, \{Bruno J.\} and Dutliff Boshoff and Hancke, \{Gerhard P.\}",

year = "2023",

doi = "10.1109/IECON51785.2023.10311874",

language = "English",

isbn = "979-8-3503-3183-7",

series = "IECON Proceedings (Industrial Electronics Conference)",

publisher = "IEEE",

booktitle = "IECON 2023 - 49th Annual Conference of the IEEE Industrial Electronics Society",

address = "United States",

note = "49th Annual Conference of the IEEE Industrial Electronics Society (IECON 2023), IEEE IECON 2023 ; Conference date: 16-10-2023 Through 19-10-2023",

url = "https://www.iecon2023.org/",

}

Nkrow, RE, Silva, BJ, Boshoff, D & Hancke, GP 2023, UWB-Based NLOS Identification and Mitigation: A Performance Evaluation in Dynamic Settings. in IECON 2023 - 49th Annual Conference of the IEEE Industrial Electronics Society. IECON Proceedings (Industrial Electronics Conference), IEEE, 49th Annual Conference of the IEEE Industrial Electronics Society (IECON 2023), Singapore, 16/10/23. https://doi.org/10.1109/IECON51785.2023.10311874

UWB-Based NLOS Identification and Mitigation: A Performance Evaluation in Dynamic Settings. / Nkrow, Raphael E.; Silva, Bruno J.; Boshoff, Dutliff et al.
IECON 2023 - 49th Annual Conference of the IEEE Industrial Electronics Society. IEEE, 2023. (IECON Proceedings (Industrial Electronics Conference)).

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

TY - GEN

T1 - UWB-Based NLOS Identification and Mitigation

T2 - 49th Annual Conference of the IEEE Industrial Electronics Society (IECON 2023)

AU - Nkrow, Raphael E.

AU - Silva, Bruno J.

AU - Boshoff, Dutliff

AU - Hancke, Gerhard P.

PY - 2023

Y1 - 2023

N2 - In the fourth industrial revolution (Industry 4.0), robotics and autonomous navigational systems are essential for smart agriculture. Industrial smart agriculture relies heavily on autonomous navigational systems, which have important uses in unmanned farms, industrial supply chains, etc. For effective navigation of autonomous robotic systems in industrial settings, indoor-based positioning and navigation technologies play key roles. However, positioning performance is severely impacted by the abundance of Non-Line-Of-Sight (NLOS) components due to the dynamic nature of industrial environments. Different approaches have been proposed in literature for identifying and mitigating NLOS components in UWB positioning systems. However, the performance of these proposed approaches on par in multiple distinct environments is unknown. In this paper, we experimentally investigate and compare the performance of recent UWB-based state-of-the-art approaches to NLOS identification and mitigation on par, in distinct and dynamic obstructed settings to ascertain two key insights: i) how the performance of existing approaches change based on the environment type; ii) the impact of the environment type on NLOS identification and mitigation. © 2023 IEEE.

AB - In the fourth industrial revolution (Industry 4.0), robotics and autonomous navigational systems are essential for smart agriculture. Industrial smart agriculture relies heavily on autonomous navigational systems, which have important uses in unmanned farms, industrial supply chains, etc. For effective navigation of autonomous robotic systems in industrial settings, indoor-based positioning and navigation technologies play key roles. However, positioning performance is severely impacted by the abundance of Non-Line-Of-Sight (NLOS) components due to the dynamic nature of industrial environments. Different approaches have been proposed in literature for identifying and mitigating NLOS components in UWB positioning systems. However, the performance of these proposed approaches on par in multiple distinct environments is unknown. In this paper, we experimentally investigate and compare the performance of recent UWB-based state-of-the-art approaches to NLOS identification and mitigation on par, in distinct and dynamic obstructed settings to ascertain two key insights: i) how the performance of existing approaches change based on the environment type; ii) the impact of the environment type on NLOS identification and mitigation. © 2023 IEEE.

KW - Localization

KW - NLOS

KW - Ranging

KW - Time-of-Flight

UR - https://www.scopus.com/pages/publications/85179510595

UR - https://www.scopus.com/pages/publications/85179510595#tab=impact

U2 - 10.1109/IECON51785.2023.10311874

DO - 10.1109/IECON51785.2023.10311874

M3 - RGC 32 - Refereed conference paper (with host publication)

SN - 979-8-3503-3183-7

T3 - IECON Proceedings (Industrial Electronics Conference)

BT - IECON 2023 - 49th Annual Conference of the IEEE Industrial Electronics Society

PB - IEEE

Y2 - 16 October 2023 through 19 October 2023

ER -

UWB-Based NLOS Identification and Mitigation: A Performance Evaluation in Dynamic Settings

Abstract

Publication series

Conference

Funding

UN SDGs

Research Keywords

Publisher's Copyright Statement

RGC Funding Information

Access Output

Other Access Options

Permanent Link

Other Files and Links

Fingerprint

GRF: Designing Distance-Bounding Protocols Resilient to Time-of-Flight Errors

Cite this

UWB-Based NLOS Identification and Mitigation: A Performance Evaluation in Dynamic Settings

Abstract

Publication series

Conference

Funding

UN SDGs

Research Keywords

Publisher's Copyright Statement

RGC Funding Information

Access Output

Other Access Options

Permanent Link

Other Files and Links

Fingerprint

Projects

GRF: Designing Distance-Bounding Protocols Resilient to Time-of-Flight Errors

Cite this