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Research ArticleOriginal Article
Open Access

Real-Time Ionosphere Prediction Based on IGS Rapid Products Using Long Short-Term Memory Deep Learning

Jianping Chen and Yang Gao
NAVIGATION: Journal of the Institute of Navigation June 2023, 70 (2) navi.581; DOI: https://doi.org/10.33012/navi.581
Jianping Chen
Department of Geomatics Engineering, University of Calgary
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  • For correspondence: [email protected]
Yang Gao
Department of Geomatics Engineering, University of Calgary
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Article Information

vol. 70 no. 2 navi.581
DOI 
https://doi.org/10.33012/navi.581

Published By 
Institute of Navigation
Print ISSN 
0028-1522
Online ISSN 
2161-4296
History 
  • Received May 10, 2022
  • Revision received November 24, 2022
  • Accepted February 4, 2023
  • Published online March 28, 2023.

Copyright & Usage 
© 2023 Institute of Navigation This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

Author Information

  1. Jianping Chen⇑ and
  2. Yang Gao
  1. Department of Geomatics Engineering, University of Calgary
  1. Correspondence
    Jianping Chen, 2500 University Dr. NW, Calgary, AB Canada T2N 1N4. Email: jian.chen1{at}ucalgary.ca
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NAVIGATION: Journal of the Institute of Navigation: 70 (2)
NAVIGATION: Journal of the Institute of Navigation
Vol. 70, Issue 2
Summer 2023
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Real-Time Ionosphere Prediction Based on IGS Rapid Products Using Long Short-Term Memory Deep Learning
Jianping Chen, Yang Gao
NAVIGATION: Journal of the Institute of Navigation Jun 2023, 70 (2) navi.581; DOI: 10.33012/navi.581

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Real-Time Ionosphere Prediction Based on IGS Rapid Products Using Long Short-Term Memory Deep Learning
Jianping Chen, Yang Gao
NAVIGATION: Journal of the Institute of Navigation Jun 2023, 70 (2) navi.581; DOI: 10.33012/navi.581
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  • Article
    • Abstract
    • 1 INTRODUCTION
    • 2 METHODOLOGY
    • 3 EXPERIMENTS AND RESULTS
    • 4 EVALUATION OF PROPOSED IONOSPHERE MODEL IN SINGLE-FREQUENCY STANDARD POINT POSITIONING (SPP)
    • 5 CONCLUSION
    • HOW TO CITE THIS ARTICLE
    • CONFLICT OF INTEREST
    • ACKNOWLEDGMENTS
    • REFERENCES
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More in this TOC Section

  • Candidate Design of New Service Signals in the NavIC L1 Frequency Band
  • Thirty Years of Maintaining WGS 84 with GPS
  • Doppler Positioning Using Multi-Constellation LEO Satellite Broadband Signals as Signals of Opportunity
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Keywords

  • deep learning
  • Ionospheric prediction
  • LSTM
  • neural network

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