Abstract
one-step matching algorithm, guide star catalog Abstract. An algorithm based on the primary star, called the two-step matching algorithm, is proposed. The recognition characteristic of this algorithm consists of angular distances between the primary star and its neighboring stars, and the directions of neighbor stars. This algorithm uses star map information with high efficiency. The performan ce of the algorithm is analyzed through a simulation experiment that compares it with grid algorithm and another algorithm based on the primary star. Simulation results show that the correct identification rate of the two-step matching algorithm is more than 98% when the standard deviation of Gaussian noise is 2 pixels. This algorithm is robust with fake stars and magnitude deviation. The identification rate is more than 96% when five fake stars are present in the star maps. In addition, the algorithm has many advantages, such as quick identification, being unaffected by magnitude noise, and having a small guide star catalog. The two-step matching algorithm has good application value and is promising in the area of star identification. aerospace industry. The working processes of the star sensor include preprocessing of star maps, star point extraction, star identification, and attitude determination. Star identification is a crucial link directly related to star sensor performance. Star identification finds the unique characteristic and can distinguish different star maps. The undirected star maps are matched with the guide star catalog using the unique characteristic. The corresponding relations among stars in the field of view (FOV) of the star sensor and the guide catalog can be determined. Numerous star identification algorithms can be broadly divided into two classes (3,4) . The first class is the subgraph isomorphism algorithms. These algorithms extract geometric characteristic using stars and the angular distance among them as vertices and edges. The formed polygons or match groups are used to perform star identification in this fashion in such algorithms. Traditional star identification algorithms, such as angular distance algorithm (5,6) , triangle algorithm (7-9) , quadrilateral algorithm (10) , and match group algorithm (11,12) , belong to this class. The second class comprises algorithms that use star
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
