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A SPEARMAN CORRELATION BASED STAR PATTERN RECOGNITION

Abstract: 

High accuracy is required for determining the orientation of a satellite in space. Amongst the existing sensors, a star tracker provides a very high accuracy of attitude determination. When no prior attitude is available, it operates in the “Lost-In-Space (LIS)” mode. Star pattern recognition is the most crucial part of a star tracker in the LIS mode. In this paper, a novel star pattern recognition approach is proposed, which constructs a signal from the features extracted in the star image and utilizes spearman correlation for identifying the correct stars. The proposed technique achieves a high identification accuracy of 99.67%. The results from the simulations show that this technique is also highly recognition reliable to the cases of missing stars, deviation in star positions, magnitude uncertainty, and false stars compared to the existing star identification algorithms.

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Paper Details

Authors:
Shoushun Chen
Submitted On:
8 September 2017 - 12:08am
Short Link:
Type:
Poster
Event:
Presenter's Name:
Deval Mehta
Paper Code:
1390
Document Year:
2017
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POSTER.pdf

(569 downloads)

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[1] Shoushun Chen, "A SPEARMAN CORRELATION BASED STAR PATTERN RECOGNITION", IEEE SigPort, 2017. [Online]. Available: http://sigport.org/1864. Accessed: Sep. 19, 2017.
@article{1864-17,
url = {http://sigport.org/1864},
author = {Shoushun Chen },
publisher = {IEEE SigPort},
title = {A SPEARMAN CORRELATION BASED STAR PATTERN RECOGNITION},
year = {2017} }
TY - EJOUR
T1 - A SPEARMAN CORRELATION BASED STAR PATTERN RECOGNITION
AU - Shoushun Chen
PY - 2017
PB - IEEE SigPort
UR - http://sigport.org/1864
ER -
Shoushun Chen. (2017). A SPEARMAN CORRELATION BASED STAR PATTERN RECOGNITION. IEEE SigPort. http://sigport.org/1864
Shoushun Chen, 2017. A SPEARMAN CORRELATION BASED STAR PATTERN RECOGNITION. Available at: http://sigport.org/1864.
Shoushun Chen. (2017). "A SPEARMAN CORRELATION BASED STAR PATTERN RECOGNITION." Web.
1. Shoushun Chen. A SPEARMAN CORRELATION BASED STAR PATTERN RECOGNITION [Internet]. IEEE SigPort; 2017. Available from : http://sigport.org/1864