Singular value decomposition-based robust cubature Kalman filtering for an integrated GPS/SINS navigation system

Singular value decomposition-based robust cubature Kalman filtering for an integrated GPS/SINS navigation system

A new nonlinear robust filter is proposed in this paper to deal with the outliers of an integrated Global Positioning System/Strapdown Inertial Navigation System (GPS/SINS) navigation system. The influence of different design parameters for an H∞ cubature Kalman filter is analysed. It is found that...

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Main Authors: Zhang, Qiuzhao, Meng, Xiaolin, Zhang, Shubi, Wang, Yunjia
Format: Article
Language:English
Published: Cambridge University Press 2015
Online Access:http://eprints.nottingham.ac.uk/35396/
http://eprints.nottingham.ac.uk/35396/
http://eprints.nottingham.ac.uk/35396/
http://eprints.nottingham.ac.uk/35396/1/SVD-based%20robust%20CKF%20for%20an%20integrated%20GPS%20SINS%20navigation%20system%20for%20JoN%2020140411.pdf
id nottingham-35396
recordtype eprints
spelling nottingham-353962018-06-26T12:35:23Z http://eprints.nottingham.ac.uk/35396/ Singular value decomposition-based robust cubature Kalman filtering for an integrated GPS/SINS navigation system Zhang, Qiuzhao Meng, Xiaolin Zhang, Shubi Wang, Yunjia A new nonlinear robust filter is proposed in this paper to deal with the outliers of an integrated Global Positioning System/Strapdown Inertial Navigation System (GPS/SINS) navigation system. The influence of different design parameters for an H∞ cubature Kalman filter is analysed. It is found that when the design parameter is small, the robustness of the filter is stronger. However, the design parameter is easily out of step in the Riccati equation and the filter easily diverges. In this respect, a singular value decomposition algorithm is employed to replace the Cholesky decomposition in the robust cubature Kalman filter. With large conditions for the design parameter, the new filter is more robust. The test results demonstrate that the proposed filter algorithm is more reliable and effective in dealing with the outliers in the data sets produced by the integrated GPS/SINS system. Cambridge University Press 2015-05 Article PeerReviewed application/pdf en http://eprints.nottingham.ac.uk/35396/1/SVD-based%20robust%20CKF%20for%20an%20integrated%20GPS%20SINS%20navigation%20system%20for%20JoN%2020140411.pdf Zhang, Qiuzhao and Meng, Xiaolin and Zhang, Shubi and Wang, Yunjia (2015) Singular value decomposition-based robust cubature Kalman filtering for an integrated GPS/SINS navigation system. Journal of Navigation, 68 (03). pp. 549-562. ISSN 1469-7785 http://journals.cambridge.org/action/displayAbstract?fromPage=online&aid=9623825&fileId=S0373463314000812 doi:10.1017/S0373463314000812 doi:10.1017/S0373463314000812
repository_type Digital Repository
institution_category Local University
institution University of Nottingham Malaysia Campus
building Nottingham Research Data Repository
collection Online Access
language English
description A new nonlinear robust filter is proposed in this paper to deal with the outliers of an integrated Global Positioning System/Strapdown Inertial Navigation System (GPS/SINS) navigation system. The influence of different design parameters for an H∞ cubature Kalman filter is analysed. It is found that when the design parameter is small, the robustness of the filter is stronger. However, the design parameter is easily out of step in the Riccati equation and the filter easily diverges. In this respect, a singular value decomposition algorithm is employed to replace the Cholesky decomposition in the robust cubature Kalman filter. With large conditions for the design parameter, the new filter is more robust. The test results demonstrate that the proposed filter algorithm is more reliable and effective in dealing with the outliers in the data sets produced by the integrated GPS/SINS system.
format Article
author Zhang, Qiuzhao
Meng, Xiaolin
Zhang, Shubi
Wang, Yunjia
spellingShingle Zhang, Qiuzhao
Meng, Xiaolin
Zhang, Shubi
Wang, Yunjia
Singular value decomposition-based robust cubature Kalman filtering for an integrated GPS/SINS navigation system
author_facet Zhang, Qiuzhao
Meng, Xiaolin
Zhang, Shubi
Wang, Yunjia
author_sort Zhang, Qiuzhao
title Singular value decomposition-based robust cubature Kalman filtering for an integrated GPS/SINS navigation system
title_short Singular value decomposition-based robust cubature Kalman filtering for an integrated GPS/SINS navigation system
title_full Singular value decomposition-based robust cubature Kalman filtering for an integrated GPS/SINS navigation system
title_fullStr Singular value decomposition-based robust cubature Kalman filtering for an integrated GPS/SINS navigation system
title_full_unstemmed Singular value decomposition-based robust cubature Kalman filtering for an integrated GPS/SINS navigation system
title_sort singular value decomposition-based robust cubature kalman filtering for an integrated gps/sins navigation system
publisher Cambridge University Press
publishDate 2015
url http://eprints.nottingham.ac.uk/35396/
http://eprints.nottingham.ac.uk/35396/
http://eprints.nottingham.ac.uk/35396/
http://eprints.nottingham.ac.uk/35396/1/SVD-based%20robust%20CKF%20for%20an%20integrated%20GPS%20SINS%20navigation%20system%20for%20JoN%2020140411.pdf
first_indexed 2018-09-06T12:35:08Z
last_indexed 2018-09-06T12:35:08Z
_version_ 1610861572113039360

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