A New Star Identification Algorithm Based on Fuzzy Algorithms

  • Shahin Sohrabi
  • Ali Asghar Beheshti Shirazi
Conference paper
Part of the Advances in Intelligent and Soft Computing book series (AINSC, volume 95)


The proposed algorithm is for satellite attitude determination. In this algorithm, the star point pattern convert to line pattern by “Delaunay triangulation” method, then we present a fuzzy line pattern matching. In this method, we use the membership functions to describe position, orientation and relation similarities between different line segments. The simulation results based on the “Desktop Universes Star images” demonstrate that the fuzzy star pattern recognition algorithm speeds up the process of star identification and increases the rate of success greatly (96.4%) compared with traditional matching algorithms. In addition, since the quality of star images play an important role in improving accuracy of star pattern recognition algorithm, therefore for image pre-processing we propose a fuzzy edge detection technique. This method highly affects noise cancellation, star features extraction, database production and matching algorithm.


Membership Function Delaunay Triangulation Line Pattern Attitude Determination Noise Cancellation 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Shahin Sohrabi
    • 1
  • Ali Asghar Beheshti Shirazi
    • 2
  1. 1.Iran University of Science and TechnologyIran
  2. 2.Engineering groupIran University of Science and TechnologyIran

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