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Fault Detection and Exclusion Method for a Deeply Integrated BDS/INS System
The Inertial Navigation System (INS) is often fused with the Global Navigation Satellite System (GNSS) to provide more robust and superior navigation service, especially in degraded signal environments. Compared with loosely and tightly coupled architectures, the Deep Integration (DI) architecture h...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7180497/ https://www.ncbi.nlm.nih.gov/pubmed/32224953 http://dx.doi.org/10.3390/s20071844 |
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author | Sun, Junren Niu, Zun Zhu, Bocheng |
author_facet | Sun, Junren Niu, Zun Zhu, Bocheng |
author_sort | Sun, Junren |
collection | PubMed |
description | The Inertial Navigation System (INS) is often fused with the Global Navigation Satellite System (GNSS) to provide more robust and superior navigation service, especially in degraded signal environments. Compared with loosely and tightly coupled architectures, the Deep Integration (DI) architecture has better tracking and positioning performance. Information is shared among channels, and the assistant information from INS helps to reduce the dynamic stress of tracking loops. However, this vector tracking architecture may result in easy propagation of errors among tracking channels. To solve this problem, a Fault Detection and Exclusion (FDE) method for the deeply integrated BeiDou Navigation Satellite System (BDS)/INS navigation system is proposed in this paper. This method utilizes pre-filters’ outputs and integration filter’s estimations to form test statistics. These statistics can help to detect and exclude both step errors and Slowly Growing Errors (SGEs) correctly. The monitoring capability of the method was verified by a simulation which was based on a software receiver. The simulation results show that the proposed FDE method works effectively. Additionally, the method is convenient to be implemented in real-time applications because of its simplicity. |
format | Online Article Text |
id | pubmed-7180497 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-71804972020-05-01 Fault Detection and Exclusion Method for a Deeply Integrated BDS/INS System Sun, Junren Niu, Zun Zhu, Bocheng Sensors (Basel) Article The Inertial Navigation System (INS) is often fused with the Global Navigation Satellite System (GNSS) to provide more robust and superior navigation service, especially in degraded signal environments. Compared with loosely and tightly coupled architectures, the Deep Integration (DI) architecture has better tracking and positioning performance. Information is shared among channels, and the assistant information from INS helps to reduce the dynamic stress of tracking loops. However, this vector tracking architecture may result in easy propagation of errors among tracking channels. To solve this problem, a Fault Detection and Exclusion (FDE) method for the deeply integrated BeiDou Navigation Satellite System (BDS)/INS navigation system is proposed in this paper. This method utilizes pre-filters’ outputs and integration filter’s estimations to form test statistics. These statistics can help to detect and exclude both step errors and Slowly Growing Errors (SGEs) correctly. The monitoring capability of the method was verified by a simulation which was based on a software receiver. The simulation results show that the proposed FDE method works effectively. Additionally, the method is convenient to be implemented in real-time applications because of its simplicity. MDPI 2020-03-26 /pmc/articles/PMC7180497/ /pubmed/32224953 http://dx.doi.org/10.3390/s20071844 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 Sun, Junren Niu, Zun Zhu, Bocheng Fault Detection and Exclusion Method for a Deeply Integrated BDS/INS System |
title | Fault Detection and Exclusion Method for a Deeply Integrated BDS/INS System |
title_full | Fault Detection and Exclusion Method for a Deeply Integrated BDS/INS System |
title_fullStr | Fault Detection and Exclusion Method for a Deeply Integrated BDS/INS System |
title_full_unstemmed | Fault Detection and Exclusion Method for a Deeply Integrated BDS/INS System |
title_short | Fault Detection and Exclusion Method for a Deeply Integrated BDS/INS System |
title_sort | fault detection and exclusion method for a deeply integrated bds/ins system |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7180497/ https://www.ncbi.nlm.nih.gov/pubmed/32224953 http://dx.doi.org/10.3390/s20071844 |
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