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Improving the Strapdown Airborne Vector Gravimetry by a Backward Inertial Navigation Algorithm
Strapdown airborne gravimetry is an efficient way to obtain gravity field data. A new method has been developed to improve the accuracy of airborne vector gravimetry. The method introduces a backward strapdown navigation algorithm into the strapdown gravimetry, which is the reverse process of forwar...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6308597/ https://www.ncbi.nlm.nih.gov/pubmed/30558217 http://dx.doi.org/10.3390/s18124432 |
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author | Wang, Minghao Cao, Juliang Cai, Shaokun Wu, Meiping Zhang, Kaidong Yu, Ruihang |
author_facet | Wang, Minghao Cao, Juliang Cai, Shaokun Wu, Meiping Zhang, Kaidong Yu, Ruihang |
author_sort | Wang, Minghao |
collection | PubMed |
description | Strapdown airborne gravimetry is an efficient way to obtain gravity field data. A new method has been developed to improve the accuracy of airborne vector gravimetry. The method introduces a backward strapdown navigation algorithm into the strapdown gravimetry, which is the reverse process of forward algorithm. Compared with the forward algorithm, the backward algorithm has the same performance in the condition of no sensor error, but has different error characteristics in actual conditions. The differences of the two algorithms in the strapdown gravimetry data processing are presented by simulations, which show that the two algorithms have different performance in the horizontal attitude measurement and convergence of integrated navigation filter. On the basis of detailed analysis, the procedures of accuracy improvement method are presented. The result of this method is very promising when applying to an actual flight test carried out by a SGA-WZ02 strapdown gravimeter. After applying the proposed method, the repeatability of two gravity disturbance horizontal components were 1.83 mGal and 1.80 mGal under the resolution of 6 km, which validate the effectiveness of the method. Furthermore, the wavenumber correlation filter is also discussed as an alternative data fusion method. |
format | Online Article Text |
id | pubmed-6308597 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-63085972019-01-04 Improving the Strapdown Airborne Vector Gravimetry by a Backward Inertial Navigation Algorithm Wang, Minghao Cao, Juliang Cai, Shaokun Wu, Meiping Zhang, Kaidong Yu, Ruihang Sensors (Basel) Article Strapdown airborne gravimetry is an efficient way to obtain gravity field data. A new method has been developed to improve the accuracy of airborne vector gravimetry. The method introduces a backward strapdown navigation algorithm into the strapdown gravimetry, which is the reverse process of forward algorithm. Compared with the forward algorithm, the backward algorithm has the same performance in the condition of no sensor error, but has different error characteristics in actual conditions. The differences of the two algorithms in the strapdown gravimetry data processing are presented by simulations, which show that the two algorithms have different performance in the horizontal attitude measurement and convergence of integrated navigation filter. On the basis of detailed analysis, the procedures of accuracy improvement method are presented. The result of this method is very promising when applying to an actual flight test carried out by a SGA-WZ02 strapdown gravimeter. After applying the proposed method, the repeatability of two gravity disturbance horizontal components were 1.83 mGal and 1.80 mGal under the resolution of 6 km, which validate the effectiveness of the method. Furthermore, the wavenumber correlation filter is also discussed as an alternative data fusion method. MDPI 2018-12-14 /pmc/articles/PMC6308597/ /pubmed/30558217 http://dx.doi.org/10.3390/s18124432 Text en © 2018 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 Wang, Minghao Cao, Juliang Cai, Shaokun Wu, Meiping Zhang, Kaidong Yu, Ruihang Improving the Strapdown Airborne Vector Gravimetry by a Backward Inertial Navigation Algorithm |
title | Improving the Strapdown Airborne Vector Gravimetry by a Backward Inertial Navigation Algorithm |
title_full | Improving the Strapdown Airborne Vector Gravimetry by a Backward Inertial Navigation Algorithm |
title_fullStr | Improving the Strapdown Airborne Vector Gravimetry by a Backward Inertial Navigation Algorithm |
title_full_unstemmed | Improving the Strapdown Airborne Vector Gravimetry by a Backward Inertial Navigation Algorithm |
title_short | Improving the Strapdown Airborne Vector Gravimetry by a Backward Inertial Navigation Algorithm |
title_sort | improving the strapdown airborne vector gravimetry by a backward inertial navigation algorithm |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6308597/ https://www.ncbi.nlm.nih.gov/pubmed/30558217 http://dx.doi.org/10.3390/s18124432 |
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