• Title of article

    Error analysis of satellite attitude determination using a vision-based approach

  • Author/Authors

    Carozza، نويسنده , , Ludovico and Bevilacqua، نويسنده , , Alessandro، نويسنده ,

  • Issue Information
    روزنامه با شماره پیاپی سال 2013
  • Pages
    11
  • From page
    19
  • To page
    29
  • Abstract
    Improvements in communication and processing technologies have opened the doors to exploit on-board cameras to compute objects’ spatial attitude using only the visual information from sequences of remote sensed images. The strategies and the algorithmic approach used to extract such information affect the estimation accuracy of the three-axis orientation of the object. ork presents a method for analyzing the most relevant error sources, including numerical ones, possible drift effects and their influence on the overall accuracy, referring to vision-based approaches. The method in particular focuses on the analysis of the image registration algorithm, carried out through on-purpose simulations. The overall accuracy has been assessed on a challenging case study, for which accuracy represents the fundamental requirement. In particular, attitude determination has been analyzed for small satellites, by comparing theoretical findings to metric results from simulations on realistic ground-truth data. Significant laboratory experiments, using a numerical control unit, have further confirmed the outcome. ieve that our analysis approach, as well as our findings in terms of error characterization, can be useful at proof-of-concept design and planning levels, since they emphasize the main sources of error for visual based approaches employed for satellite attitude estimation. Nevertheless, the approach we present is also of general interest for all the affine applicative domains which require an accurate estimation of three-dimensional orientation parameters (i.e., robotics, airborne stabilization).
  • Keywords
    Satellite , feature tracking , Accuracy analysis , Error analysis , image registration , Vision
  • Journal title
    ISPRS Journal of Photogrammetry and Remote Sensing
  • Serial Year
    2013
  • Journal title
    ISPRS Journal of Photogrammetry and Remote Sensing
  • Record number

    2229316