A survey of all-sky autonomous star identification algorithms

Author

Na, Meng ; Jia, Peifa

Author_Institution

Dept. of Comput. Sci. & Technol., Tsinghua Univ., Beijing

fYear

2006

fDate

19-21 Jan. 2006

Lastpage

901

Abstract

Star sensors are widely used in aerospace and astronautics due to their high precise attitude measurements. The main difficulty when estimate a fully autonomous attitude is identifying the stars in the sensor field. This paper surveys the development of the past 35 years in the area of autonomous star identification. Some classical algorithms such as polygon algorithm, match group algorithm, grid algorithm, neural network, genetic algorithm, singular value method, and so on are reviewed and described in detail. The performances of each algorithm are compared and the factors related to the problem are analyzed. Finally, some conclusions and suggestions are given for future research

Keywords

aerospace instrumentation; attitude measurement; genetic algorithms; identification; neural nets; pattern matching; sensors; singular value decomposition; stars; all-sky autonomous star identification algorithms; attitude measurements; autonomous attitude estimation; genetic algorithm; grid algorithm; match group algorithm; neural network; polygon algorithm; singular value method; star sensors; Algorithm design and analysis; CMOS image sensors; Charge coupled devices; Charge-coupled image sensors; Extraterrestrial measurements; Genetic algorithms; Navigation; Position measurement; Sensor phenomena and characterization; Space vehicles;

fLanguage

English

Publisher

ieee

Conference_Titel

Systems and Control in Aerospace and Astronautics, 2006. ISSCAA 2006. 1st International Symposium on

Conference_Location

Harbin

Print_ISBN

0-7803-9395-3

Type

conf

DOI

10.1109/ISSCAA.2006.1627471

Filename

1627471