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A Novel Time Delay Estimation Algorithm for 5G Vehicle Positioning in Urban Canyon Environments
Vehicle positioning with 5G can effectively compensate for the lack of vehicle positioning based on GNSS (Global Navigation Satellite System) in urban canyons. However, there is also a large ranging error in the non-line of sight (NLOS) propagation of 5G. Aiming to solve this problem, we consider a...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7571156/ https://www.ncbi.nlm.nih.gov/pubmed/32932989 http://dx.doi.org/10.3390/s20185190 |
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author | Deng, Zhongliang Zheng, Xinyu Wang, Hanhua Fu, Xiao Yin, Lu Liu, Wen |
author_facet | Deng, Zhongliang Zheng, Xinyu Wang, Hanhua Fu, Xiao Yin, Lu Liu, Wen |
author_sort | Deng, Zhongliang |
collection | PubMed |
description | Vehicle positioning with 5G can effectively compensate for the lack of vehicle positioning based on GNSS (Global Navigation Satellite System) in urban canyons. However, there is also a large ranging error in the non-line of sight (NLOS) propagation of 5G. Aiming to solve this problem, we consider a new time delay estimation algorithm called non-line of sight cancellation multiple signal classification (NC-MUSIC). This algorithm uses cross-correlation to identify and cancel the NLOS signal. Then, an unsupervised multipath estimation method is used to estimate the number of multipaths and extract the noise subspace. The MUSIC spectral function can be calculated by the noise subspace. Finally, the time delay of the direct path is estimated by searching the peak of MUSIC spectral function. This paper adopts the 5G channel model developed by 3GPP TR38.901 for simulation experiments. The experiment results demonstrated that the proposed algorithm has obvious advantages in terms of NLOS propagation for urban canyon environments. It provided a high-precision time delay estimation algorithm for observed time difference of arrival (OTDOA), joint angle of arrival (AOA) ranging, and other positioning methods in the 5G vehicle positioning method, which can effectively improve the positioning accuracy of 5G vehicle positioning in urban canyon environments. |
format | Online Article Text |
id | pubmed-7571156 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-75711562020-10-28 A Novel Time Delay Estimation Algorithm for 5G Vehicle Positioning in Urban Canyon Environments Deng, Zhongliang Zheng, Xinyu Wang, Hanhua Fu, Xiao Yin, Lu Liu, Wen Sensors (Basel) Article Vehicle positioning with 5G can effectively compensate for the lack of vehicle positioning based on GNSS (Global Navigation Satellite System) in urban canyons. However, there is also a large ranging error in the non-line of sight (NLOS) propagation of 5G. Aiming to solve this problem, we consider a new time delay estimation algorithm called non-line of sight cancellation multiple signal classification (NC-MUSIC). This algorithm uses cross-correlation to identify and cancel the NLOS signal. Then, an unsupervised multipath estimation method is used to estimate the number of multipaths and extract the noise subspace. The MUSIC spectral function can be calculated by the noise subspace. Finally, the time delay of the direct path is estimated by searching the peak of MUSIC spectral function. This paper adopts the 5G channel model developed by 3GPP TR38.901 for simulation experiments. The experiment results demonstrated that the proposed algorithm has obvious advantages in terms of NLOS propagation for urban canyon environments. It provided a high-precision time delay estimation algorithm for observed time difference of arrival (OTDOA), joint angle of arrival (AOA) ranging, and other positioning methods in the 5G vehicle positioning method, which can effectively improve the positioning accuracy of 5G vehicle positioning in urban canyon environments. MDPI 2020-09-11 /pmc/articles/PMC7571156/ /pubmed/32932989 http://dx.doi.org/10.3390/s20185190 Text en © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Deng, Zhongliang Zheng, Xinyu Wang, Hanhua Fu, Xiao Yin, Lu Liu, Wen A Novel Time Delay Estimation Algorithm for 5G Vehicle Positioning in Urban Canyon Environments |
title | A Novel Time Delay Estimation Algorithm for 5G Vehicle Positioning in Urban Canyon Environments |
title_full | A Novel Time Delay Estimation Algorithm for 5G Vehicle Positioning in Urban Canyon Environments |
title_fullStr | A Novel Time Delay Estimation Algorithm for 5G Vehicle Positioning in Urban Canyon Environments |
title_full_unstemmed | A Novel Time Delay Estimation Algorithm for 5G Vehicle Positioning in Urban Canyon Environments |
title_short | A Novel Time Delay Estimation Algorithm for 5G Vehicle Positioning in Urban Canyon Environments |
title_sort | novel time delay estimation algorithm for 5g vehicle positioning in urban canyon environments |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7571156/ https://www.ncbi.nlm.nih.gov/pubmed/32932989 http://dx.doi.org/10.3390/s20185190 |
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