• 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