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A Robust INS/SRS/CNS Integrated Navigation System with the Chi-Square Test-Based Robust Kalman Filter

In order to achieve a highly autonomous and reliable navigation system for aerial vehicles that involves the spectral redshift navigation system (SRS), the inertial navigation (INS)/spectral redshift navigation (SRS)/celestial navigation (CNS) integrated system is designed and the spectral-redshift-...

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Detalles Bibliográficos
Autores principales: Gao, Guangle, Gao, Shesheng, Hong, Genyuan, Peng, Xu, Yu, Tian
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7588989/
https://www.ncbi.nlm.nih.gov/pubmed/33086757
http://dx.doi.org/10.3390/s20205909
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author Gao, Guangle
Gao, Shesheng
Hong, Genyuan
Peng, Xu
Yu, Tian
author_facet Gao, Guangle
Gao, Shesheng
Hong, Genyuan
Peng, Xu
Yu, Tian
author_sort Gao, Guangle
collection PubMed
description In order to achieve a highly autonomous and reliable navigation system for aerial vehicles that involves the spectral redshift navigation system (SRS), the inertial navigation (INS)/spectral redshift navigation (SRS)/celestial navigation (CNS) integrated system is designed and the spectral-redshift-based velocity measurement equation in the INS/SRS/CNS system is derived. Furthermore, a new chi-square test-based robust Kalman filter (CSTRKF) is also proposed in order to improve the robustness of the INS/SRS/CNS navigation system. In the CSTRKF, the chi-square test (CST) not only detects measurements with outliers and in non-Gaussian distributions, but also estimates the statistical characteristics of measurement noise. Finally, the results of our simulations indicate that the INS/SRS/CNS integrated navigation system with the CSTRKF possesses strong robustness and high reliability.
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spelling pubmed-75889892020-10-29 A Robust INS/SRS/CNS Integrated Navigation System with the Chi-Square Test-Based Robust Kalman Filter Gao, Guangle Gao, Shesheng Hong, Genyuan Peng, Xu Yu, Tian Sensors (Basel) Article In order to achieve a highly autonomous and reliable navigation system for aerial vehicles that involves the spectral redshift navigation system (SRS), the inertial navigation (INS)/spectral redshift navigation (SRS)/celestial navigation (CNS) integrated system is designed and the spectral-redshift-based velocity measurement equation in the INS/SRS/CNS system is derived. Furthermore, a new chi-square test-based robust Kalman filter (CSTRKF) is also proposed in order to improve the robustness of the INS/SRS/CNS navigation system. In the CSTRKF, the chi-square test (CST) not only detects measurements with outliers and in non-Gaussian distributions, but also estimates the statistical characteristics of measurement noise. Finally, the results of our simulations indicate that the INS/SRS/CNS integrated navigation system with the CSTRKF possesses strong robustness and high reliability. MDPI 2020-10-19 /pmc/articles/PMC7588989/ /pubmed/33086757 http://dx.doi.org/10.3390/s20205909 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
Gao, Guangle
Gao, Shesheng
Hong, Genyuan
Peng, Xu
Yu, Tian
A Robust INS/SRS/CNS Integrated Navigation System with the Chi-Square Test-Based Robust Kalman Filter
title A Robust INS/SRS/CNS Integrated Navigation System with the Chi-Square Test-Based Robust Kalman Filter
title_full A Robust INS/SRS/CNS Integrated Navigation System with the Chi-Square Test-Based Robust Kalman Filter
title_fullStr A Robust INS/SRS/CNS Integrated Navigation System with the Chi-Square Test-Based Robust Kalman Filter
title_full_unstemmed A Robust INS/SRS/CNS Integrated Navigation System with the Chi-Square Test-Based Robust Kalman Filter
title_short A Robust INS/SRS/CNS Integrated Navigation System with the Chi-Square Test-Based Robust Kalman Filter
title_sort robust ins/srs/cns integrated navigation system with the chi-square test-based robust kalman filter
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7588989/
https://www.ncbi.nlm.nih.gov/pubmed/33086757
http://dx.doi.org/10.3390/s20205909
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