Volume 44 Issue 11
Dec.  2015
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Sun Jianming. Application of subdivision feature set of star pattern recognition method in astronomical navigation[J]. Infrared and Laser Engineering, 2015, 44(11): 3330-3335.
Citation: Sun Jianming. Application of subdivision feature set of star pattern recognition method in astronomical navigation[J]. Infrared and Laser Engineering, 2015, 44(11): 3330-3335.

Application of subdivision feature set of star pattern recognition method in astronomical navigation

  • Received Date: 2015-03-20
  • Rev Recd Date: 2015-04-03
  • Publish Date: 2015-11-25
  • A star pattern recognition method based on subdivisiom feature set was proposed in order to quickly and efficiently recognize star pattern and accurately complete celestial navigation task. Firstly, a database was built by star data, on which feature star database was established by triangulation. Then subdivision feature of star pattern could be compared, which will be recognized, with feature star database and implement star pattern recognition. By improving some similar methods like Hamming similarity and Euclid similarity, a new star pattern recognition method was put forward based on triangulation feature set, by which a very small possible star set could be found. This process can be repeated to obtain adjacent possible star set. In these two star sets, the nearest star between right ascension and declination was the one recognized. Experiments show that accuracy rate can reach more than 97% by using this method, and the star pattern recognition task can be completed accurately.
  • [1] Mao Haicen, Liu Aidong, Wang Liang. Star recognition method based on hybrid particle swarm optimization algorithm[J]. Infrared and Laser Engineering, 2014, 43(11): 3762-3766. (in Chinese)
    [2] Wei Wei, Liu Enhai. Preprocessing of infrared star map and position accuracy analysis of star point[J]. Infrared and Laser Engineering, 2014, 43(3): 991-996. (in Chinese)
    [3] Yoon H, Paek S W, Lim Y, et al. New star pattern identification with vector pattern matching for attitude determination[J]. Aerospace and Electronic Systems, IEEE Transactions on, 2013, 49(2): 1108-1118.
    [4] Fan Qiaoyun, Lu Zhuangzhi, Wei Xinguo, et al. Triangle star identification algorithm based on inertia ratio[J]. Infrared and Laser Engineering, 2012, 41(10): 2838-2843. (in Chinese)
    [5] Shaodi Z, Yanjie W, Honghai S. Application of triangulation and PSO-BP neural network to star pattern recognition[J]. Opto-Electronic Engineering, 2011, 38(6): 30-37.
    [6] Yoon H, Lim Y, Bang H. New star-pattern identification using a correlation approach for spacecraft attitude determination[J]. Journal of Spacecraft and Rockets, 2011, 48(1): 182-186.
    [7] Kim J W, Lee G, Moon S M, et al. Metabolomic screening and star pattern recognition by urinary amino acid profile analysis from bladder cancer patients[J]. Metabolomics, 2010, 6(2): 202-206.
    [8] Pei Ran, Hou Yushi, Hao Yong, et al. A star identification algorithm based on group-matching[C]//Mechatronic Sciences, Electric Engineering and Computer(MEC), Proceedings 2013 International Conference on IEEE, 2013: 1502-1505.
    [9] Mao Yue, Song Xiaoyong, Feng Laiping. Visibility analysis of X-ray pulsar navigation[J]. Geomatics and Information Science of Wuhan University, 2009, 34(2): 222-225. (in Chinese)
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Application of subdivision feature set of star pattern recognition method in astronomical navigation

  • 1. School of Computer and Information Engineering,Harbin University of Commerce,Harbin 150028,China

Abstract: A star pattern recognition method based on subdivisiom feature set was proposed in order to quickly and efficiently recognize star pattern and accurately complete celestial navigation task. Firstly, a database was built by star data, on which feature star database was established by triangulation. Then subdivision feature of star pattern could be compared, which will be recognized, with feature star database and implement star pattern recognition. By improving some similar methods like Hamming similarity and Euclid similarity, a new star pattern recognition method was put forward based on triangulation feature set, by which a very small possible star set could be found. This process can be repeated to obtain adjacent possible star set. In these two star sets, the nearest star between right ascension and declination was the one recognized. Experiments show that accuracy rate can reach more than 97% by using this method, and the star pattern recognition task can be completed accurately.

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