Star sensors are widely used in aerospace and astronautics due to their high precise attitude measurements. The main difficulty when estimate a fully autonomous attitude is identifying the stars in the sensor field. This paper surveys the development of the past 35 years in the area of autonomous star identification. Some classical algorithms such as polygon algorithm, match group algorithm, grid algorithm, neural network, genetic algorithm, singular value method, and so on are reviewed and described in detail. The performances of each algorithm are compared and the factors related to the problem are analyzed. Finally, some conclusions and suggestions are given for future research.


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    Title :

    A survey of all-sky autonomous star identification algorithms


    Contributors:
    Meng Na, (author) / Peifa Jia, (author)


    Publication date :

    2006-01-01


    Size :

    4960979 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English