DocumentCode :
569598
Title :
An improved star identification method based on neural network
Author :
Jing, Yang ; Liang, Wang
Author_Institution :
Sci. & Technol. on Aircraft Control Lab., Beihang Univ., Beijing, China
fYear :
2012
fDate :
25-27 July 2012
Firstpage :
118
Lastpage :
123
Abstract :
In order to increase the star identification speed and recognition rate of star sensor, an improved rapid star identification method based on neural network (NN) is presented. The proposed method is composed of three levels, including the coarse classification of navigation stars, star pattern recognition based on NN and the final validation of recognition results. The angular distance of characteristic triangle is employed for coarse classification to active the subnets for star pattern recognition. Then the star pattern obtained by the grid method for the main star is sent to the corresponding subnets for the star pattern identification. At last, the identification results of the active subnets are validated to obtain the only recognition result. The experimental results show that, compared with traditional triangle identification method, the proposed method has higher accurate recognition rate, lower redundancy and better robustness.
Keywords :
astronomy computing; neural nets; pattern classification; stars; NN-based star pattern recognition; active subnets; angular distance; coarse classification; navigation stars coarse classification; neural network-based improved star identification method; star identification recognition rate; star identification speed; star sensor; triangle identification method; Artificial neural networks; Catalogs; Character recognition; Classification algorithms; Databases; Navigation; Training; Navigation Star database; Neural Network; Star Identification; Star Sensor;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Industrial Informatics (INDIN), 2012 10th IEEE International Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4673-0312-5
Type :
conf
DOI :
10.1109/INDIN.2012.6301126
Filename :
6301126
Link To Document :
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