Title :
A survey of all-sky autonomous star identification algorithms
Author :
Na, Meng ; Jia, Peifa
Author_Institution :
Dept. of Comput. Sci. & Technol., Tsinghua Univ., Beijing
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;
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
DOI :
10.1109/ISSCAA.2006.1627471
