Singular value decomposition‐based iterative robust cubature Kalman filtering and its application for integrated global positioning system/strapdown inertial navigation system navigation

Abstract The issue of non‐linear robust state estimation in the integration of a strapdown inertial navigation system and global positioning system is addressed in this study. Based on the cubature Kalman filtering frame, a non‐linear robust filter called a robust cubature Kalman filter (RCKF) was i...

Descripción completa

Guardado en:

Detalles Bibliográficos
Autores principales:	Zhangjun Yu, Qiuzhao Zhang, Yunrui Zhang, Nanshan Zheng, Vladimír Sedlák
Formato:	article
Lenguaje:	EN
Publicado:	Wiley 2021
Materias:	cubature Kalman filter integrated navigation system non‐linear filter singular value decomposition Telecommunication TK5101-6720
Acceso en línea:	https://doaj.org/article/0de40ac2aa19493fa4bda097024472c7
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

id	oai:doaj.org-article:0de40ac2aa19493fa4bda097024472c7
record_format	dspace
spelling	oai:doaj.org-article:0de40ac2aa19493fa4bda097024472c72021-11-12T15:34:30ZSingular value decomposition‐based iterative robust cubature Kalman filtering and its application for integrated global positioning system/strapdown inertial navigation system navigation1751-87921751-878410.1049/rsn2.12160https://doaj.org/article/0de40ac2aa19493fa4bda097024472c72021-12-01T00:00:00Zhttps://doi.org/10.1049/rsn2.12160https://doaj.org/toc/1751-8784https://doaj.org/toc/1751-8792Abstract The issue of non‐linear robust state estimation in the integration of a strapdown inertial navigation system and global positioning system is addressed in this study. Based on the cubature Kalman filtering frame, a non‐linear robust filter called a robust cubature Kalman filter (RCKF) was introduced to address the outliers and the inaccurate model. It has been found that the determination of an optimal restriction parameter is crucial for maintaining the robustness and accuracy of the non‐linear robust filter. Unfortunately, the value of this restriction parameter is always determined by experience. In this study, an iterative strategy was proposed to adaptively attain the optimal restriction parameter without much previous experience. To improve the computational stability of the iterative non‐linear robust filter, a singular value decomposition strategy was adopted simultaneously. Two case studies indicate that the iterative RCKF can achieve greater robustness and accuracy using the methodology discussed in this study.Zhangjun YuQiuzhao ZhangYunrui ZhangNanshan ZhengVladimír SedlákWileyarticlecubature Kalman filterintegrated navigation systemnon‐linear filtersingular value decompositionTelecommunicationTK5101-6720ENIET Radar, Sonar & Navigation, Vol 15, Iss 12, Pp 1727-1735 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	cubature Kalman filter integrated navigation system non‐linear filter singular value decomposition Telecommunication TK5101-6720
spellingShingle	cubature Kalman filter integrated navigation system non‐linear filter singular value decomposition Telecommunication TK5101-6720 Zhangjun Yu Qiuzhao Zhang Yunrui Zhang Nanshan Zheng Vladimír Sedlák Singular value decomposition‐based iterative robust cubature Kalman filtering and its application for integrated global positioning system/strapdown inertial navigation system navigation
description	Abstract The issue of non‐linear robust state estimation in the integration of a strapdown inertial navigation system and global positioning system is addressed in this study. Based on the cubature Kalman filtering frame, a non‐linear robust filter called a robust cubature Kalman filter (RCKF) was introduced to address the outliers and the inaccurate model. It has been found that the determination of an optimal restriction parameter is crucial for maintaining the robustness and accuracy of the non‐linear robust filter. Unfortunately, the value of this restriction parameter is always determined by experience. In this study, an iterative strategy was proposed to adaptively attain the optimal restriction parameter without much previous experience. To improve the computational stability of the iterative non‐linear robust filter, a singular value decomposition strategy was adopted simultaneously. Two case studies indicate that the iterative RCKF can achieve greater robustness and accuracy using the methodology discussed in this study.
format	article
author	Zhangjun Yu Qiuzhao Zhang Yunrui Zhang Nanshan Zheng Vladimír Sedlák
author_facet	Zhangjun Yu Qiuzhao Zhang Yunrui Zhang Nanshan Zheng Vladimír Sedlák
author_sort	Zhangjun Yu
title	Singular value decomposition‐based iterative robust cubature Kalman filtering and its application for integrated global positioning system/strapdown inertial navigation system navigation
title_short	Singular value decomposition‐based iterative robust cubature Kalman filtering and its application for integrated global positioning system/strapdown inertial navigation system navigation
title_full	Singular value decomposition‐based iterative robust cubature Kalman filtering and its application for integrated global positioning system/strapdown inertial navigation system navigation
title_fullStr	Singular value decomposition‐based iterative robust cubature Kalman filtering and its application for integrated global positioning system/strapdown inertial navigation system navigation
title_full_unstemmed	Singular value decomposition‐based iterative robust cubature Kalman filtering and its application for integrated global positioning system/strapdown inertial navigation system navigation
title_sort	singular value decomposition‐based iterative robust cubature kalman filtering and its application for integrated global positioning system/strapdown inertial navigation system navigation
publisher	Wiley
publishDate	2021
url	https://doaj.org/article/0de40ac2aa19493fa4bda097024472c7
work_keys_str_mv	AT zhangjunyu singularvaluedecompositionbasediterativerobustcubaturekalmanfilteringanditsapplicationforintegratedglobalpositioningsystemstrapdowninertialnavigationsystemnavigation AT qiuzhaozhang singularvaluedecompositionbasediterativerobustcubaturekalmanfilteringanditsapplicationforintegratedglobalpositioningsystemstrapdowninertialnavigationsystemnavigation AT yunruizhang singularvaluedecompositionbasediterativerobustcubaturekalmanfilteringanditsapplicationforintegratedglobalpositioningsystemstrapdowninertialnavigationsystemnavigation AT nanshanzheng singularvaluedecompositionbasediterativerobustcubaturekalmanfilteringanditsapplicationforintegratedglobalpositioningsystemstrapdowninertialnavigationsystemnavigation AT vladimirsedlak singularvaluedecompositionbasediterativerobustcubaturekalmanfilteringanditsapplicationforintegratedglobalpositioningsystemstrapdowninertialnavigationsystemnavigation
_version_	1718430354065326080

Singular value decomposition‐based iterative robust cubature Kalman filtering and its application for integrated global positioning system/strapdown inertial navigation system navigation

Ejemplares similares