Application of Adaptive Robust CKF in SINS/GPS Initial Alignment with Large Azimuth Misalignment Angle

When the strapdown inertial navigation system does not perform coarse alignment, the misalignment angle is generally a large angle, and a nonlinear error model and a nonlinear filtering method are required. For large azimuth misalignment, the initial alignment technology with a large azimuth misalig...

Full description

Bibliographic Details
Main Authors: Zhang Bing, Wang Xiaodong, Lu Hao, Hao Zhaojun, Gu Changchao
Format: Article
Language:English
Published: Hindawi Limited 2021-01-01
Series:Mathematical Problems in Engineering
Online Access:http://dx.doi.org/10.1155/2021/7398706
id doaj-be451bb11c5b4bc9afd04f6126720971
record_format Article
spelling doaj-be451bb11c5b4bc9afd04f61267209712021-10-04T01:57:36ZengHindawi LimitedMathematical Problems in Engineering1563-51472021-01-01202110.1155/2021/7398706Application of Adaptive Robust CKF in SINS/GPS Initial Alignment with Large Azimuth Misalignment AngleZhang Bing0Wang Xiaodong1Lu Hao2Hao Zhaojun3Gu Changchao4Systems Engineering Research InstituteSystems Engineering Research InstituteSystems Engineering Research InstituteSystems Engineering Research InstituteChina Academy of Launch Vehicle TechnologyWhen the strapdown inertial navigation system does not perform coarse alignment, the misalignment angle is generally a large angle, and a nonlinear error model and a nonlinear filtering method are required. For large azimuth misalignment, the initial alignment technology with a large azimuth misalignment angle is researched in this paper. The initial alignment technology with a large azimuth misalignment angle is researched in this paper. First, the SINS/GPS nonlinear error model is established. Secondly, in the view of observation gross errors and inaccurate noise statistical characteristics, an adaptive robust CKF algorithm is proposed. Finally, according to the simulation analysis and experiment, the adaptive robust CKF algorithm can augment the stability and improve the filter estimation precision and convergence rate.http://dx.doi.org/10.1155/2021/7398706
collection DOAJ
language English
format Article
sources DOAJ
author Zhang Bing
Wang Xiaodong
Lu Hao
Hao Zhaojun
Gu Changchao
spellingShingle Zhang Bing
Wang Xiaodong
Lu Hao
Hao Zhaojun
Gu Changchao
Application of Adaptive Robust CKF in SINS/GPS Initial Alignment with Large Azimuth Misalignment Angle
Mathematical Problems in Engineering
author_facet Zhang Bing
Wang Xiaodong
Lu Hao
Hao Zhaojun
Gu Changchao
author_sort Zhang Bing
title Application of Adaptive Robust CKF in SINS/GPS Initial Alignment with Large Azimuth Misalignment Angle
title_short Application of Adaptive Robust CKF in SINS/GPS Initial Alignment with Large Azimuth Misalignment Angle
title_full Application of Adaptive Robust CKF in SINS/GPS Initial Alignment with Large Azimuth Misalignment Angle
title_fullStr Application of Adaptive Robust CKF in SINS/GPS Initial Alignment with Large Azimuth Misalignment Angle
title_full_unstemmed Application of Adaptive Robust CKF in SINS/GPS Initial Alignment with Large Azimuth Misalignment Angle
title_sort application of adaptive robust ckf in sins/gps initial alignment with large azimuth misalignment angle
publisher Hindawi Limited
series Mathematical Problems in Engineering
issn 1563-5147
publishDate 2021-01-01
description When the strapdown inertial navigation system does not perform coarse alignment, the misalignment angle is generally a large angle, and a nonlinear error model and a nonlinear filtering method are required. For large azimuth misalignment, the initial alignment technology with a large azimuth misalignment angle is researched in this paper. The initial alignment technology with a large azimuth misalignment angle is researched in this paper. First, the SINS/GPS nonlinear error model is established. Secondly, in the view of observation gross errors and inaccurate noise statistical characteristics, an adaptive robust CKF algorithm is proposed. Finally, according to the simulation analysis and experiment, the adaptive robust CKF algorithm can augment the stability and improve the filter estimation precision and convergence rate.
url http://dx.doi.org/10.1155/2021/7398706
work_keys_str_mv AT zhangbing applicationofadaptiverobustckfinsinsgpsinitialalignmentwithlargeazimuthmisalignmentangle
AT wangxiaodong applicationofadaptiverobustckfinsinsgpsinitialalignmentwithlargeazimuthmisalignmentangle
AT luhao applicationofadaptiverobustckfinsinsgpsinitialalignmentwithlargeazimuthmisalignmentangle
AT haozhaojun applicationofadaptiverobustckfinsinsgpsinitialalignmentwithlargeazimuthmisalignmentangle
AT guchangchao applicationofadaptiverobustckfinsinsgpsinitialalignmentwithlargeazimuthmisalignmentangle
_version_ 1716844764959080448