Proceedings of the 2016 5th International Conference on Measurement, Instrumentation and Automation (ICMIA 2016)

Star image identification uninfluenced by rotation

Authors
Di Jiang, Ke Zhang, Meibo Lv
Corresponding Author
Di Jiang
Available Online November 2016.
DOI
10.2991/icmia-16.2016.121How to use a DOI?
Keywords
Image identification; rotation; star sensor; guide catalog
Abstract

All-sky autonomous star map identification has come up with higher requirement on calculating speed and storage space. Error caused by rotation and location noise influences the performance of star image identification algorithms. So various algorithms include procedure of rotating star image to the position where the algorithm plans. That will have a negative effect on enhancing the performance of identification. This paper presented a recognition method uninfluenced by rotation. The rotation error is eliminated automatically in recognition course. Both position and magnitude information are considered in it. The simulation result indicates that it cost less storage space and the accuracy was increased.

Copyright
© 2016, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 2016 5th International Conference on Measurement, Instrumentation and Automation (ICMIA 2016)
Series
Advances in Intelligent Systems Research
Publication Date
November 2016
ISBN
10.2991/icmia-16.2016.121
ISSN
1951-6851
DOI
10.2991/icmia-16.2016.121How to use a DOI?
Copyright
© 2016, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Di Jiang
AU  - Ke Zhang
AU  - Meibo Lv
PY  - 2016/11
DA  - 2016/11
TI  - Star image identification uninfluenced by rotation
BT  - Proceedings of the 2016 5th International Conference on Measurement, Instrumentation and Automation (ICMIA 2016)
PB  - Atlantis Press
SN  - 1951-6851
UR  - https://doi.org/10.2991/icmia-16.2016.121
DO  - 10.2991/icmia-16.2016.121
ID  - Jiang2016/11
ER  -