Repository logo

Infoscience

  • English
  • French
Log In
Logo EPFL, École polytechnique fédérale de Lausanne

Infoscience

  • English
  • French
Log In
  1. Home
  2. Academic and Research Output
  3. Conferences, Workshops, Symposiums, and Seminars
  4. Innovation vs Residual KF Based GNSS/INS Autonomous Integrity Monitoring in Single Fault Scenario
 
conference paper

Innovation vs Residual KF Based GNSS/INS Autonomous Integrity Monitoring in Single Fault Scenario

Garcia Crespillo, Omar  
•
Grosch, Anja
•
Skaloud, Jan  
Show more
2017
Proceedings of the 30th International Technical Meeting of The Satellite Division of the Institute of Navigation
ION GNSS+ 2017

We perform a comparison between an innovation and a residual based integrity monitoring in Extended Kalman Filters for the GNSS/INS hybridization. In this paper, we restrict the study to the detection of abrupt snapshot faults in order to get an intuitive insight. We study the differences in the distribution of the test statistics and the computation of the thresholds. We derive and compare the minimum detectable bias and we provide expressions for the protection levels for both approaches in the single fault situation. We compare them with the classical residual based GNSS RAIM algorithm. Additionally, we perform a sensitivity analysis of the integrity relevant parameters to the inertial sensor quality.

  • Details
  • Metrics
Type
conference paper
Author(s)
Garcia Crespillo, Omar  
Grosch, Anja
Skaloud, Jan  
Meurer, Michael
Date Issued

2017

Published in
Proceedings of the 30th International Technical Meeting of The Satellite Division of the Institute of Navigation
Start page

2126

End page

2136

Subjects

toponav

•

integration

•

navigation

•

integrity

•

filtering

URL

URL

https://www.ion.org/publications/abstract.cfm?articleID=15136
Editorial or Peer reviewed

NON-REVIEWED

Written at

EPFL

EPFL units
TOPO  
Event nameEvent placeEvent date
ION GNSS+ 2017

Portland, Oregon, USA

September 26-29, 2017

Available on Infoscience
January 16, 2018
Use this identifier to reference this record
https://infoscience.epfl.ch/handle/20.500.14299/144195
Logo EPFL, École polytechnique fédérale de Lausanne
  • Contact
  • infoscience@epfl.ch

  • Follow us on Facebook
  • Follow us on Instagram
  • Follow us on LinkedIn
  • Follow us on X
  • Follow us on Youtube
AccessibilityLegal noticePrivacy policyCookie settingsEnd User AgreementGet helpFeedback

Infoscience is a service managed and provided by the Library and IT Services of EPFL. © EPFL, tous droits réservés