A new method of star catalog optimization for multi-FOV star sensor

Author

Junpeng Hua ; Tao Zhang ; Hailong Zhu ; Bin Liang ; Bo Liu ; Jiemei Liang

Author_Institution

Dept. of Autom., Tsinghua Univ., Beijing, China

fYear

2014

Firstpage

3529

Lastpage

3533

Abstract

A new method of star catalog optimization for multi-FOV star sensor is presented. Compared with single-FOV star sensor, multi-FOV star sensor has higher attitude accuracy and update frequency. By conducting Monte Carlo Simulation and labelling stars based on magnitude, the optimization of guide star catalog reduces the size of the catalog and improves the uniformity of the catalog, which is more suitable for multi-FOV star sensor. Test results show that the accuracy rate of the star recognition algorithm using the new catalog is higher than 95%, which can meet the requirement of the actual design. Further, in respects of storage space of the star catalog and the search speed, the new method of catalog optimization based on simulation and marking is superior to other methods under the same conditions.

Keywords

Monte Carlo methods; aerospace instrumentation; attitude measurement; optimisation; star trackers; Monte Carlo simulation; guide star catalog optimization method; multiFOV star sensor; search speed; single-FOV star sensor; spacecraft attitude measuring device; star recognition algorithm; Accuracy; Algorithm design and analysis; Catalogs; Labeling; Monte Carlo methods; Optimization; Pattern recognition; multi-FOV; star catalog; star pattern recognition; star sensor;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Control and Automation (WCICA), 2014 11th World Congress on

Type

conf

DOI

10.1109/WCICA.2014.7053302

Filename

7053302