Position, Navigation, and Timing (PNT) Through Low Earth Orbit (LEO) Satellites: A Survey on Current Status, Challenges, and Opportunities-Reference-Cited by-同舟云学术

Position, Navigation, and Timing (PNT) Through Low Earth Orbit (LEO) Satellites: A Survey on Current Status, Challenges, and Opportunities

Published:2022 Issue: Volume:10 Page:83971-84002
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Prol F. S.¹^ORCID,Ferre R. Morales²^ORCID,Saleem Z.³,Valisuo P.⁴,Pinell C.¹^ORCID,Lohan E. S.²^ORCID,Elsanhoury M.⁴^ORCID,Elmusrati M.⁴^ORCID,Islam S.¹^ORCID,Celikbilek K.²^ORCID,Selvan K.⁴,Yliaho J.⁵,Rutledge K.⁴,Ojala A.⁶^ORCID,Ferranti L.³,Praks J.³^ORCID,Bhuiyan M. Z. H.¹^ORCID,Kaasalainen S.¹^ORCID,Kuusniemi H.¹^ORCID

Affiliation:

1. Department of Navigation and Positioning, Finnish Geospatial Research Institute (FGI), National Land Survey of Finland (NLS), Espoo, Finland

2. Faculty of Information Technology and Communication Sciences, Electrical Engineering Unit, Tampere University, Tampere, Finland

3. Department of Radio Science and Engineering, Aalto University, Espoo, Finland

4. School of Technology and Innovation, University of Vaasa, Vaasa, Finland

5. Digital Economy Research Platform, University of Vaasa, Vaasa, Finland

6. School of Marketing and Communication, University of Vaasa, Vaasa, Finland

Funder

INdoor Navigation from CUBesAT Technology (INCUBATE) Project through the Technology Industries of Finland Centennial Foundation

Jane and Aatos Erko Foundation

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/6287639/9668973/09840374.pdf?arnumber=9840374

Reference206 articles.

1. Particle filters for positioning, navigation, and tracking

2. Information fusion in navigation systems via factor graph based incremental smoothing

3. Particle Filters: A Hands-On Tutorial

4. Particle swarm optimization

5. Expectation-Maximization for Adaptive Mixture Models in Graph Optimization

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