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NAVIGATION: Journal of the Institute of Navigation

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Research ArticleOriginal Article
Open Access

Improved Automatic Detection of GPS Satellite Oscillator Anomaly using a Machine Learning Algorithm

Yunxiang Liu, and Y. Jade Morton
NAVIGATION: Journal of the Institute of Navigation March 2022, 69 (1) navi.500; DOI: https://doi.org/10.33012/navi.500
Yunxiang Liu,
Smead Aerospace Engineering Sciences Department, University of Colorado, Boulder Boulder, CO, USA
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Y. Jade Morton
Smead Aerospace Engineering Sciences Department, University of Colorado, Boulder Boulder, CO, USA
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NAVIGATION: Journal of the Institute of Navigation: 69 (1)
NAVIGATION: Journal of the Institute of Navigation
Vol. 69, Issue 1
Spring 2022
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Improved Automatic Detection of GPS Satellite Oscillator Anomaly using a Machine Learning Algorithm
Yunxiang Liu,, Y. Jade Morton
NAVIGATION: Journal of the Institute of Navigation Mar 2022, 69 (1) navi.500; DOI: 10.33012/navi.500

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Improved Automatic Detection of GPS Satellite Oscillator Anomaly using a Machine Learning Algorithm
Yunxiang Liu,, Y. Jade Morton
NAVIGATION: Journal of the Institute of Navigation Mar 2022, 69 (1) navi.500; DOI: 10.33012/navi.500
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    • Abstract
    • 1 INTRODUCTION
    • 2 METHODOLOGY
    • 3 DATA SET DESCRIPTION AND PERFORMANCE EVALUATION
    • 4 DETECTION RESULTS
    • 5 CONCLUSION AND FUTURE WORK
    • HOW TO CITE THIS ARTICLE
    • ACKNOWLEDGMENTS
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Keywords

  • global monitoring system
  • GPS
  • machine learning
  • phase scintillation
  • random forest
  • satellite oscillator anomaly
  • signal quality monitoring
  • support vector machine

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