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Research ArticleOriginal Article
Open Access

Case study of Bayesian RAIM algorithm integrated with Spatial Feature Constraint and Fault Detection and Exclusion algorithms for multi-sensor positioning

Jelena Gabela, Allison Kealy, Mark Hedley and Bill Moran
NAVIGATION: Journal of the Institute of Navigation June 2021, 68 (2) 333-351; DOI: https://doi.org/10.1002/navi.433
Jelena Gabela
1Department of Electrical and Electronic Engineering, University of Melbourne, Victoria, Australia
2Department of Geospatial Science, Royal Melbourne Institute of Technology, Victoria, Australia
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Allison Kealy
2Department of Geospatial Science, Royal Melbourne Institute of Technology, Victoria, Australia
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Mark Hedley
3Data 61, Commonwealth Scientific and Industrial Research Organisation, New South Wales, Australia
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Bill Moran
1Department of Electrical and Electronic Engineering, University of Melbourne, Victoria, Australia
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NAVIGATION: Journal of the Institute of Navigation: 68 (2)
NAVIGATION: Journal of the Institute of Navigation
Vol. 68, Issue 2
Summer 2021
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Case study of Bayesian RAIM algorithm integrated with Spatial Feature Constraint and Fault Detection and Exclusion algorithms for multi-sensor positioning
Jelena Gabela, Allison Kealy, Mark Hedley, Bill Moran
NAVIGATION: Journal of the Institute of Navigation Jun 2021, 68 (2) 333-351; DOI: 10.1002/navi.433

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Case study of Bayesian RAIM algorithm integrated with Spatial Feature Constraint and Fault Detection and Exclusion algorithms for multi-sensor positioning
Jelena Gabela, Allison Kealy, Mark Hedley, Bill Moran
NAVIGATION: Journal of the Institute of Navigation Jun 2021, 68 (2) 333-351; DOI: 10.1002/navi.433
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    • Abstract
    • 1 INTRODUCTION
    • 2 MATHEMATICAL FRAMEWORK
    • 3 EXPERIMENTAL VALIDATION AND PERFORMANCE EVALUATION METRICS
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Keywords

  • Bayesian Receiver Autonomous Integrity Monitoring
  • GNSS
  • Local Positioning System
  • multi-sensor positioning
  • particle filter
  • Spatial Feature Constraint

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