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Fault Detection and Exclusion for Tightly Coupled GNSS/INS System Considering Fault in State Prediction
To ensure navigation integrity for safety-critical applications, this paper proposes an efficient Fault Detection and Exclusion (FDE) scheme for tightly coupled navigation system of Global Navigation Satellite Systems (GNSS) and Inertial Navigation System (INS). Special emphasis is placed on the pot...
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/PMC7036913/ https://www.ncbi.nlm.nih.gov/pubmed/31973136 http://dx.doi.org/10.3390/s20030590 |
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author | Wang, Shizhuang Zhan, Xingqun Zhai, Yawei Liu, Baoyu |
author_facet | Wang, Shizhuang Zhan, Xingqun Zhai, Yawei Liu, Baoyu |
author_sort | Wang, Shizhuang |
collection | PubMed |
description | To ensure navigation integrity for safety-critical applications, this paper proposes an efficient Fault Detection and Exclusion (FDE) scheme for tightly coupled navigation system of Global Navigation Satellite Systems (GNSS) and Inertial Navigation System (INS). Special emphasis is placed on the potential faults in the Kalman Filter state prediction step (defined as “filter fault”), which could be caused by the undetected faults occurring previously or the Inertial Measurement Unit (IMU) failures. The integration model is derived first to capture the features and impacts of GNSS faults and filter fault. To accommodate various fault conditions, two independent detectors, which are respectively designated for GNSS fault and filter fault, are rigorously established based on hypothesis-test methods. Following a detection event, the newly-designed exclusion function enables (a) identifying and removing the faulty measurements and (b) eliminating the effect of filter fault through filter recovery. Moreover, we also attempt to avoid wrong exclusion events by analyzing the underlying causes and optimizing the decision strategy for GNSS fault exclusion accordingly. The FDE scheme is validated through multiple simulations, where high efficiency and effectiveness have been achieved in various fault scenarios. |
format | Online Article Text |
id | pubmed-7036913 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-70369132020-03-11 Fault Detection and Exclusion for Tightly Coupled GNSS/INS System Considering Fault in State Prediction Wang, Shizhuang Zhan, Xingqun Zhai, Yawei Liu, Baoyu Sensors (Basel) Article To ensure navigation integrity for safety-critical applications, this paper proposes an efficient Fault Detection and Exclusion (FDE) scheme for tightly coupled navigation system of Global Navigation Satellite Systems (GNSS) and Inertial Navigation System (INS). Special emphasis is placed on the potential faults in the Kalman Filter state prediction step (defined as “filter fault”), which could be caused by the undetected faults occurring previously or the Inertial Measurement Unit (IMU) failures. The integration model is derived first to capture the features and impacts of GNSS faults and filter fault. To accommodate various fault conditions, two independent detectors, which are respectively designated for GNSS fault and filter fault, are rigorously established based on hypothesis-test methods. Following a detection event, the newly-designed exclusion function enables (a) identifying and removing the faulty measurements and (b) eliminating the effect of filter fault through filter recovery. Moreover, we also attempt to avoid wrong exclusion events by analyzing the underlying causes and optimizing the decision strategy for GNSS fault exclusion accordingly. The FDE scheme is validated through multiple simulations, where high efficiency and effectiveness have been achieved in various fault scenarios. MDPI 2020-01-21 /pmc/articles/PMC7036913/ /pubmed/31973136 http://dx.doi.org/10.3390/s20030590 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 Wang, Shizhuang Zhan, Xingqun Zhai, Yawei Liu, Baoyu Fault Detection and Exclusion for Tightly Coupled GNSS/INS System Considering Fault in State Prediction |
title | Fault Detection and Exclusion for Tightly Coupled GNSS/INS System Considering Fault in State Prediction |
title_full | Fault Detection and Exclusion for Tightly Coupled GNSS/INS System Considering Fault in State Prediction |
title_fullStr | Fault Detection and Exclusion for Tightly Coupled GNSS/INS System Considering Fault in State Prediction |
title_full_unstemmed | Fault Detection and Exclusion for Tightly Coupled GNSS/INS System Considering Fault in State Prediction |
title_short | Fault Detection and Exclusion for Tightly Coupled GNSS/INS System Considering Fault in State Prediction |
title_sort | fault detection and exclusion for tightly coupled gnss/ins system considering fault in state prediction |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7036913/ https://www.ncbi.nlm.nih.gov/pubmed/31973136 http://dx.doi.org/10.3390/s20030590 |
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