Grid algorithm is a classical algorithm for all-sky autonomous star identification. However its recognition rate decreases rapidly when the position and magnitude noise increases in the star image. In order to overcome this problem, a modified grid algorithm called the "elastic gray grid algorithm" is proposed. Gray pattern and elastic template matching are introduced into the grid algorithm to enhance its ability to tolerate the position and magnitude noise. Experimental results show that the modified grid algorithm performs better compared with the original one. The elastic gray grid algorithm reached up to a 100% recognition rate under random positional noise in our test bed. Furthermore it increases the original recognition rate from 69.86% to 97%, under the same condition, for both the position and the magnitude noise.


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    Titel :

    Modified Grid Algorithm for Noisy All-Sky Autonomous Star Identification


    Beteiligte:
    Meng Na, (Autor:in) / Danian Zheng, (Autor:in) / Peifa Jia, (Autor:in)


    Erscheinungsdatum :

    01.04.2009


    Format / Umfang :

    1282585 byte




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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