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Comparison of Kalman Filters for Inertial Integrated Navigation
The current research on integrated navigation is mainly focused on filtering or integrated navigation equipment. Studies systematically comparing and analyzing how to choose appropriate integrated filtering methods under different circumstances are lacking. This paper focuses on integrated navigatio...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6470584/ https://www.ncbi.nlm.nih.gov/pubmed/30909502 http://dx.doi.org/10.3390/s19061426 |
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author | Zhang, Mengde Li, Kailong Hu, Baiqing Meng, Chunjian |
author_facet | Zhang, Mengde Li, Kailong Hu, Baiqing Meng, Chunjian |
author_sort | Zhang, Mengde |
collection | PubMed |
description | The current research on integrated navigation is mainly focused on filtering or integrated navigation equipment. Studies systematically comparing and analyzing how to choose appropriate integrated filtering methods under different circumstances are lacking. This paper focuses on integrated navigation filters that are used by different filters and attitude parameters for inertial integrated navigation. We researched integrated navigation filters, established algorithms, and examined the relative merits for practical integrated navigation. Some suggestions for the use of filtering algorithms are provided. We completed simulations and car-mounted experiments for low-cost strapdown inertial navigation system (SINS) to assess the performance of the integrated navigation filtering algorithms. |
format | Online Article Text |
id | pubmed-6470584 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-64705842019-04-26 Comparison of Kalman Filters for Inertial Integrated Navigation Zhang, Mengde Li, Kailong Hu, Baiqing Meng, Chunjian Sensors (Basel) Article The current research on integrated navigation is mainly focused on filtering or integrated navigation equipment. Studies systematically comparing and analyzing how to choose appropriate integrated filtering methods under different circumstances are lacking. This paper focuses on integrated navigation filters that are used by different filters and attitude parameters for inertial integrated navigation. We researched integrated navigation filters, established algorithms, and examined the relative merits for practical integrated navigation. Some suggestions for the use of filtering algorithms are provided. We completed simulations and car-mounted experiments for low-cost strapdown inertial navigation system (SINS) to assess the performance of the integrated navigation filtering algorithms. MDPI 2019-03-22 /pmc/articles/PMC6470584/ /pubmed/30909502 http://dx.doi.org/10.3390/s19061426 Text en © 2019 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 Zhang, Mengde Li, Kailong Hu, Baiqing Meng, Chunjian Comparison of Kalman Filters for Inertial Integrated Navigation |
title | Comparison of Kalman Filters for Inertial Integrated Navigation |
title_full | Comparison of Kalman Filters for Inertial Integrated Navigation |
title_fullStr | Comparison of Kalman Filters for Inertial Integrated Navigation |
title_full_unstemmed | Comparison of Kalman Filters for Inertial Integrated Navigation |
title_short | Comparison of Kalman Filters for Inertial Integrated Navigation |
title_sort | comparison of kalman filters for inertial integrated navigation |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6470584/ https://www.ncbi.nlm.nih.gov/pubmed/30909502 http://dx.doi.org/10.3390/s19061426 |
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