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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...

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Detalles Bibliográficos
Autores principales: Zhang, Mengde, Li, Kailong, Hu, Baiqing, Meng, Chunjian
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2019
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.
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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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AT hubaiqing comparisonofkalmanfiltersforinertialintegratednavigation
AT mengchunjian comparisonofkalmanfiltersforinertialintegratednavigation