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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...

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Autores principales: Wang, Shizhuang, Zhan, Xingqun, Zhai, Yawei, Liu, Baoyu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
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.
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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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