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Robust SCKF Filtering Method for MINS/GPS In-Motion Alignment

This paper presents a novel multiple strong tracking adaptive square-root cubature Kalman filter (MSTASCKF) based on the frame of the Sage–Husa filter, employing the multi-fading factor which could automatically adjust the Q value according to the rapidly changing noise in the flight process. This f...

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Detalles Bibliográficos
Autores principales: Zhang, Huanrui, Zhang, Xiaoyue
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8068010/
https://www.ncbi.nlm.nih.gov/pubmed/33917236
http://dx.doi.org/10.3390/s21082597
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author Zhang, Huanrui
Zhang, Xiaoyue
author_facet Zhang, Huanrui
Zhang, Xiaoyue
author_sort Zhang, Huanrui
collection PubMed
description This paper presents a novel multiple strong tracking adaptive square-root cubature Kalman filter (MSTASCKF) based on the frame of the Sage–Husa filter, employing the multi-fading factor which could automatically adjust the Q value according to the rapidly changing noise in the flight process. This filter can estimate the system noise in real-time during the filtering process and adjust the system noise variance matrix Q so that the filtering accuracy is not significantly reduced with the noise. At the same time, the residual error in the filtering process is used as a measure of the filtering effect, and a multiple fading factor is introduced to adjust the posterior error variance matrix in the filtering process, so that the residual error is always orthogonal and the stability of the filtering is maintained. Finally, a vibration test is designed which simulates the random noise of the short-range guided weapon in flight through the shaking table and adds the noise to the present simulation trajectory for semi-physical simulation. The simulation results show that the proposed filter can significantly reduce the attitude estimation error caused by random vibration.
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spelling pubmed-80680102021-04-25 Robust SCKF Filtering Method for MINS/GPS In-Motion Alignment Zhang, Huanrui Zhang, Xiaoyue Sensors (Basel) Communication This paper presents a novel multiple strong tracking adaptive square-root cubature Kalman filter (MSTASCKF) based on the frame of the Sage–Husa filter, employing the multi-fading factor which could automatically adjust the Q value according to the rapidly changing noise in the flight process. This filter can estimate the system noise in real-time during the filtering process and adjust the system noise variance matrix Q so that the filtering accuracy is not significantly reduced with the noise. At the same time, the residual error in the filtering process is used as a measure of the filtering effect, and a multiple fading factor is introduced to adjust the posterior error variance matrix in the filtering process, so that the residual error is always orthogonal and the stability of the filtering is maintained. Finally, a vibration test is designed which simulates the random noise of the short-range guided weapon in flight through the shaking table and adds the noise to the present simulation trajectory for semi-physical simulation. The simulation results show that the proposed filter can significantly reduce the attitude estimation error caused by random vibration. MDPI 2021-04-07 /pmc/articles/PMC8068010/ /pubmed/33917236 http://dx.doi.org/10.3390/s21082597 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/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 (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Communication
Zhang, Huanrui
Zhang, Xiaoyue
Robust SCKF Filtering Method for MINS/GPS In-Motion Alignment
title Robust SCKF Filtering Method for MINS/GPS In-Motion Alignment
title_full Robust SCKF Filtering Method for MINS/GPS In-Motion Alignment
title_fullStr Robust SCKF Filtering Method for MINS/GPS In-Motion Alignment
title_full_unstemmed Robust SCKF Filtering Method for MINS/GPS In-Motion Alignment
title_short Robust SCKF Filtering Method for MINS/GPS In-Motion Alignment
title_sort robust sckf filtering method for mins/gps in-motion alignment
topic Communication
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8068010/
https://www.ncbi.nlm.nih.gov/pubmed/33917236
http://dx.doi.org/10.3390/s21082597
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