Star extraction based on clustering within a star tracker

Abstract

The traditional star extraction methods of star tracker need much processing time and large image memory, resulting in slow attitude acquisition and complex electronic circuits. A new star extraction method, star extraction based on clustering, was developed. The analysis of on-line background estimation algorithm and clustering algorithm in the new method was introduced. The method was realized in one of the novel star trackers developed by Beijing Institute of Control Engineering (BICE), on-board circumlunar return and reentry spacecraft of 3rd phase of China lunar exploration program. According to the house-keeping data packages recorded during on-ground real sky test and the flight mission, the processing time of star extraction was reduced by 84% at least and the image memory was reduced by 99% at least, compared with traditional methods. The results indicated that the star extraction based on clustering had advantages in processing time, memory and migration,which made it possible to realize the method in almost all kinds of optical sensors.