A planet centroid is an important observable object in autonomous optical navigation. A high-accuracy algorithm is presented to extract the planet centroid from its raw image. First, we proposed a planet segmentation algorithm to segment the planet image block to eliminate noise and to reduce the computation load. Second, we developed an effective algorithm based on Prewitt-Zernike moments to detect sub-pixel real edges by determining possible edges with the Prewitt operator, removing pseudo-edges in backlit shady areas, and relocating real edges to a sub-pixel accuracy in the Zernike moments. Third, we proposed an elliptical model to fit sub-pixel edge points. Finally, we verified the performance of this algorithm against real images from the Cassini-Huygens mission and against synthetic simulated images. Simulation results showed that the accuracy of the planet centroid is up to 0·3 pixels and that of the line-of-sight vector is at 2·1 × 10-5 rad.


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    Title :

    A High-accuracy Extraction Algorithm of Planet Centroid Image in Deep-space Autonomous Optical Navigation



    Published in:

    Publication date :

    2016




    Type of media :

    Article (Journal)


    Type of material :

    Print


    Language :

    English



    Classification :

    BKL:    55.86 Schiffsverkehr, Schifffahrt / 53.84 Ortungstechnik, Radartechnik / 42.89 Zoologie: Sonstiges / 55.54 Flugführung / 42.89 / 53.84 / 55.20 / 55.86 / 55.20 Straßenfahrzeugtechnik / 55.44 Schiffsführung / 55.54 / 55.44
    Local classification TIB:    275/5680/7035