Fault Detection and Exclusion for Tightly Coupled GNSS/INS System Considering Fault in State Prediction.

GNSS INS fault detection and exclusion integrity monitoring kalman filter

Journal

Sensors (Basel, Switzerland)
ISSN: 1424-8220
Titre abrégé: Sensors (Basel)
Pays: Switzerland
ID NLM: 101204366

Informations de publication

Date de publication:
21 Jan 2020
Historique:
received: 03 12 2019
revised: 14 01 2020
accepted: 18 01 2020
entrez: 25 1 2020
pubmed: 25 1 2020
medline: 25 1 2020
Statut: epublish

Résumé

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.

Identifiants

pubmed: 31973136
pii: s20030590
doi: 10.3390/s20030590
pmc: PMC7036913
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Subventions

Organisme : Honeywell Technology Solutions China
ID : -

Déclaration de conflit d'intérêts

The authors declare no conflict of interest.

Références

Sensors (Basel). 2010;10(1):456-74
pubmed: 22315550
Sensors (Basel). 2018 Aug 01;18(8):
pubmed: 30071591

Auteurs

Shizhuang Wang (S)

School of Aeronautics and Astronautics, Shanghai Jiao Tong University, Shanghai 200240, China.

Xingqun Zhan (X)

School of Aeronautics and Astronautics, Shanghai Jiao Tong University, Shanghai 200240, China.

Yawei Zhai (Y)

School of Aeronautics and Astronautics, Shanghai Jiao Tong University, Shanghai 200240, China.

Baoyu Liu (B)

Schulich School of Engineering, University of Calgary, Calgary, AB T2N 1N4, Canada.

Classifications MeSH