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A Multi-Sensor Tight Fusion Method Designed for Vehicle Navigation
Using the Global Navigation Satellite System (GNSS), it is difficult to provide continuous and reliable position service for vehicle navigation in complex urban environments, due to the natural vulnerability of the GNSS signal. With the rapid development of the sensor technology and the reduction in...
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/PMC7249057/ https://www.ncbi.nlm.nih.gov/pubmed/32365805 http://dx.doi.org/10.3390/s20092551 |
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author | Lai, Qifeng Yuan, Hong Wei, Dongyan Wang, Ningbo Li, Zishen Ji, Xinchun |
author_facet | Lai, Qifeng Yuan, Hong Wei, Dongyan Wang, Ningbo Li, Zishen Ji, Xinchun |
author_sort | Lai, Qifeng |
collection | PubMed |
description | Using the Global Navigation Satellite System (GNSS), it is difficult to provide continuous and reliable position service for vehicle navigation in complex urban environments, due to the natural vulnerability of the GNSS signal. With the rapid development of the sensor technology and the reduction in their costs, the positioning performance of GNSS is expected to be significantly improved by fusing multi-sensors. In order to improve the continuity and reliability of the vehicle navigation system, we proposed a multi-sensor tight fusion (MTF) method by combining the inertial navigation system (INS), odometer, and barometric altimeter with the GNSS technique. Different fusion strategies were presented in the open-sky, insufficient satellite, and satellite outage environments to check the performance improvement of the proposed method. The simulation and real-device tests demonstrate that in the open-sky context, the error of sensors can be estimated correctly. This is useful for sensor noise compensation and position accuracy improvement, when GNSS is unavailable. In the insufficient satellite context (6 min), with the help of the barometric altimeter and a clock model, the accuracy of the method can be close to that in the open-sky context. In the satellite outage context, the error divergence of the MTF is obviously slower than the traditional GNSS/INS tightly coupled integration, as seen by odometer and barometric altimeter assisting. |
format | Online Article Text |
id | pubmed-7249057 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-72490572020-06-10 A Multi-Sensor Tight Fusion Method Designed for Vehicle Navigation Lai, Qifeng Yuan, Hong Wei, Dongyan Wang, Ningbo Li, Zishen Ji, Xinchun Sensors (Basel) Article Using the Global Navigation Satellite System (GNSS), it is difficult to provide continuous and reliable position service for vehicle navigation in complex urban environments, due to the natural vulnerability of the GNSS signal. With the rapid development of the sensor technology and the reduction in their costs, the positioning performance of GNSS is expected to be significantly improved by fusing multi-sensors. In order to improve the continuity and reliability of the vehicle navigation system, we proposed a multi-sensor tight fusion (MTF) method by combining the inertial navigation system (INS), odometer, and barometric altimeter with the GNSS technique. Different fusion strategies were presented in the open-sky, insufficient satellite, and satellite outage environments to check the performance improvement of the proposed method. The simulation and real-device tests demonstrate that in the open-sky context, the error of sensors can be estimated correctly. This is useful for sensor noise compensation and position accuracy improvement, when GNSS is unavailable. In the insufficient satellite context (6 min), with the help of the barometric altimeter and a clock model, the accuracy of the method can be close to that in the open-sky context. In the satellite outage context, the error divergence of the MTF is obviously slower than the traditional GNSS/INS tightly coupled integration, as seen by odometer and barometric altimeter assisting. MDPI 2020-04-30 /pmc/articles/PMC7249057/ /pubmed/32365805 http://dx.doi.org/10.3390/s20092551 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 Lai, Qifeng Yuan, Hong Wei, Dongyan Wang, Ningbo Li, Zishen Ji, Xinchun A Multi-Sensor Tight Fusion Method Designed for Vehicle Navigation |
title | A Multi-Sensor Tight Fusion Method Designed for Vehicle Navigation |
title_full | A Multi-Sensor Tight Fusion Method Designed for Vehicle Navigation |
title_fullStr | A Multi-Sensor Tight Fusion Method Designed for Vehicle Navigation |
title_full_unstemmed | A Multi-Sensor Tight Fusion Method Designed for Vehicle Navigation |
title_short | A Multi-Sensor Tight Fusion Method Designed for Vehicle Navigation |
title_sort | multi-sensor tight fusion method designed for vehicle navigation |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7249057/ https://www.ncbi.nlm.nih.gov/pubmed/32365805 http://dx.doi.org/10.3390/s20092551 |
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