Guest Editorial for the TAES Special Section on Machine Learning Methods for Aerial and Space Positioning and Navigation-Reference-Cited by-同舟云学术

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Guest Editorial for the TAES Special Section on Machine Learning Methods for Aerial and Space Positioning and Navigation

Published:2024-06 Issue:3 Volume:60 Page:2494-2499
ISSN:0018-9251
Container-title:IEEE Transactions on Aerospace and Electronic Systems
language:
Short-container-title:IEEE Trans. Aerosp. Electron. Syst.

Author:

Yu Kegen¹^ORCID,Dunik Jindrich²^ORCID,Braasch Michael S.³^ORCID,Closas Pau⁴^ORCID,Dovis Fabio⁵^ORCID

Affiliation:

1. School of Environment Science and Spatial Informatics, China University of Mining and Technology, Xuzhou, China

2. Department of Cybernetics, University of West Bohemia and Honeywell, Pilsen, Czech Republic

3. Avionics Engineering Center, Ohio University, Athena, OH, USA

4. Department of Electrical and Computer Engineering, Northeastern University, Boston, MA, USA

5. Department of Electronics and Telecommunications, Politecnico di Torino, Turin, Italy

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx8/7/10552647/10552652.pdf?arnumber=10552652

Reference15 articles.

1. Springer Handbook of Global Navigation Satellite Systems

2. Position, Navigation, and Timing Technologies in the 21st Century

3. Handbook of Position Location

4. Wireless Positioning: Principles and Practice

5. Vulnerabilities, threats, and authentication in satellite-based navigation systems [scanning the issue]

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