A Three-Dimensional Localization System with Distance Selection through Feature Points

Yanlin Wang; Xiaozhen Yan; Qinghua Luo; Pengtai Zhou; Jie Liu

doi:10.1109/PHM-Besancon49106.2020.00029

A Three-Dimensional Localization System with Distance Selection through Feature Points

Yanlin Wang
, Xiaozhen Yan
, Qinghua Luo
, Pengtai Zhou
, Jie Liu

School of Information Science and Engineering, Harbin Institute of Technology Weihai
Shandong Institute of Shipbuilding Technology

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

A three-dimensional localization system plays a crucial role in various application environments, including the three-dimensional warehouse, smart city, unmanned aerial vehicle (UAV) and other localization-based service systems. The propagation of wireless signal is usually sensitive to the sounding environments, which results in multi-path, none-line of sight (NLOS) and other noise; and as a result, the corresponding localization accuracy is usually low. Correspondingly, we present a three-dimensional localization system with distance selection through feature points in this paper. We first utilize a specific strategy to conduct distance estimation. Then in the localization space, we define the feature points and select the optimized feature point. Next, with the selected feature points, we evaluate the distance backward and selectively optimize the distance estimation results for localization computation. Finally, a highly accurate localization result can be obtained. The simulation and experimental results illustrate the feasibility of the proposed method.

Original language	English
Title of host publication	Proceedings - 2020 Prognostics and Health Management Conference, PHM-Besancon 2020
Editors	Jianyu Long, Zhiqiang Pu, Ping Ding
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	137-141
Number of pages	5
ISBN (Electronic)	9781728156750
DOIs	https://doi.org/10.1109/PHM-Besancon49106.2020.00029
State	Published - May 2020
Externally published	Yes
Event	2020 Prognostics and Health Management Conference, PHM-Besancon 2020 - Besancon, France Duration: 4 May 2020 → 7 May 2020

Publication series

Name	Proceedings - 2020 Prognostics and Health Management Conference, PHM-Besancon 2020

Conference

Conference	2020 Prognostics and Health Management Conference, PHM-Besancon 2020
Country/Territory	France
City	Besancon
Period	4/05/20 → 7/05/20

UN SDGs

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

SDG 11 Sustainable Cities and Communities

Keywords

Feature point
Three dimension
Wireless Localization

Access to Document

10.1109/PHM-Besancon49106.2020.00029

Cite this

Wang, Y., Yan, X., Luo, Q., Zhou, P., & Liu, J. (2020). A Three-Dimensional Localization System with Distance Selection through Feature Points. In J. Long, Z. Pu, & P. Ding (Eds.), Proceedings - 2020 Prognostics and Health Management Conference, PHM-Besancon 2020 (pp. 137-141). Article 9115561 (Proceedings - 2020 Prognostics and Health Management Conference, PHM-Besancon 2020). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/PHM-Besancon49106.2020.00029

Wang, Yanlin ; Yan, Xiaozhen ; Luo, Qinghua et al. / A Three-Dimensional Localization System with Distance Selection through Feature Points. Proceedings - 2020 Prognostics and Health Management Conference, PHM-Besancon 2020. editor / Jianyu Long ; Zhiqiang Pu ; Ping Ding. Institute of Electrical and Electronics Engineers Inc., 2020. pp. 137-141 (Proceedings - 2020 Prognostics and Health Management Conference, PHM-Besancon 2020).

@inproceedings{7d78e3aa411a452cbd10959e2a1b99a9,

title = "A Three-Dimensional Localization System with Distance Selection through Feature Points",

abstract = "A three-dimensional localization system plays a crucial role in various application environments, including the three-dimensional warehouse, smart city, unmanned aerial vehicle (UAV) and other localization-based service systems. The propagation of wireless signal is usually sensitive to the sounding environments, which results in multi-path, none-line of sight (NLOS) and other noise; and as a result, the corresponding localization accuracy is usually low. Correspondingly, we present a three-dimensional localization system with distance selection through feature points in this paper. We first utilize a specific strategy to conduct distance estimation. Then in the localization space, we define the feature points and select the optimized feature point. Next, with the selected feature points, we evaluate the distance backward and selectively optimize the distance estimation results for localization computation. Finally, a highly accurate localization result can be obtained. The simulation and experimental results illustrate the feasibility of the proposed method.",

keywords = "Feature point, Three dimension, Wireless Localization",

author = "Yanlin Wang and Xiaozhen Yan and Qinghua Luo and Pengtai Zhou and Jie Liu",

note = "Publisher Copyright: {\textcopyright} 2020 IEEE.; 2020 Prognostics and Health Management Conference, PHM-Besancon 2020 ; Conference date: 04-05-2020 Through 07-05-2020",

year = "2020",

month = may,

doi = "10.1109/PHM-Besancon49106.2020.00029",

language = "英语",

series = "Proceedings - 2020 Prognostics and Health Management Conference, PHM-Besancon 2020",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "137--141",

editor = "Jianyu Long and Zhiqiang Pu and Ping Ding",

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}

Wang, Y, Yan, X , Luo, Q, Zhou, P & Liu, J 2020, A Three-Dimensional Localization System with Distance Selection through Feature Points. in J Long, Z Pu & P Ding (eds), Proceedings - 2020 Prognostics and Health Management Conference, PHM-Besancon 2020., 9115561, Proceedings - 2020 Prognostics and Health Management Conference, PHM-Besancon 2020, Institute of Electrical and Electronics Engineers Inc., pp. 137-141, 2020 Prognostics and Health Management Conference, PHM-Besancon 2020, Besancon, France, 4/05/20. https://doi.org/10.1109/PHM-Besancon49106.2020.00029

A Three-Dimensional Localization System with Distance Selection through Feature Points. / Wang, Yanlin; Yan, Xiaozhen ; Luo, Qinghua et al.
Proceedings - 2020 Prognostics and Health Management Conference, PHM-Besancon 2020. ed. / Jianyu Long; Zhiqiang Pu; Ping Ding. Institute of Electrical and Electronics Engineers Inc., 2020. p. 137-141 9115561 (Proceedings - 2020 Prognostics and Health Management Conference, PHM-Besancon 2020).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - A Three-Dimensional Localization System with Distance Selection through Feature Points

AU - Wang, Yanlin

AU - Yan, Xiaozhen

AU - Luo, Qinghua

AU - Zhou, Pengtai

AU - Liu, Jie

PY - 2020/5

Y1 - 2020/5

N2 - A three-dimensional localization system plays a crucial role in various application environments, including the three-dimensional warehouse, smart city, unmanned aerial vehicle (UAV) and other localization-based service systems. The propagation of wireless signal is usually sensitive to the sounding environments, which results in multi-path, none-line of sight (NLOS) and other noise; and as a result, the corresponding localization accuracy is usually low. Correspondingly, we present a three-dimensional localization system with distance selection through feature points in this paper. We first utilize a specific strategy to conduct distance estimation. Then in the localization space, we define the feature points and select the optimized feature point. Next, with the selected feature points, we evaluate the distance backward and selectively optimize the distance estimation results for localization computation. Finally, a highly accurate localization result can be obtained. The simulation and experimental results illustrate the feasibility of the proposed method.

AB - A three-dimensional localization system plays a crucial role in various application environments, including the three-dimensional warehouse, smart city, unmanned aerial vehicle (UAV) and other localization-based service systems. The propagation of wireless signal is usually sensitive to the sounding environments, which results in multi-path, none-line of sight (NLOS) and other noise; and as a result, the corresponding localization accuracy is usually low. Correspondingly, we present a three-dimensional localization system with distance selection through feature points in this paper. We first utilize a specific strategy to conduct distance estimation. Then in the localization space, we define the feature points and select the optimized feature point. Next, with the selected feature points, we evaluate the distance backward and selectively optimize the distance estimation results for localization computation. Finally, a highly accurate localization result can be obtained. The simulation and experimental results illustrate the feasibility of the proposed method.

KW - Feature point

KW - Three dimension

KW - Wireless Localization

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U2 - 10.1109/PHM-Besancon49106.2020.00029

DO - 10.1109/PHM-Besancon49106.2020.00029

M3 - 会议稿件

AN - SCOPUS:85087282354

T3 - Proceedings - 2020 Prognostics and Health Management Conference, PHM-Besancon 2020

SP - 137

EP - 141

BT - Proceedings - 2020 Prognostics and Health Management Conference, PHM-Besancon 2020

A2 - Long, Jianyu

A2 - Pu, Zhiqiang

A2 - Ding, Ping

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2020 Prognostics and Health Management Conference, PHM-Besancon 2020

Y2 - 4 May 2020 through 7 May 2020

ER -

Wang Y, Yan X , Luo Q, Zhou P, Liu J. A Three-Dimensional Localization System with Distance Selection through Feature Points. In Long J, Pu Z, Ding P, editors, Proceedings - 2020 Prognostics and Health Management Conference, PHM-Besancon 2020. Institute of Electrical and Electronics Engineers Inc. 2020. p. 137-141. 9115561. (Proceedings - 2020 Prognostics and Health Management Conference, PHM-Besancon 2020). doi: 10.1109/PHM-Besancon49106.2020.00029

A Three-Dimensional Localization System with Distance Selection through Feature Points

Abstract

Publication series

Conference

UN SDGs

Keywords

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