Browse

Hardware Design and Star Selection Algorithm for Arcsecond Pico Star Tracker : 각초 별 추적기를 위한 하드웨어 설계 및 별 선택 알고리즘

Cited 0 time in Web of Science Cited 0 time in Scopus
Authors
비슈아난드
Advisor
I.S. Jeung
Major
공과대학 기계항공공학부
Issue Date
2018-02
Publisher
서울대학교 대학원
Keywords
Nano satellitesPico Star TrackerStar Selection Algorithm
Description
학위논문 (박사)-- 서울대학교 대학원 : 공과대학 기계항공공학부, 2018. 2. I.S. Jeung.
Abstract
The star tracker estimates pointing knowledge of a satellite in arcsecond accuracy in three axes without apriori knowledge. But star trackers are larger in size, heavier, power hungry and expensive for nanosatellite missions. The Arcsecond Pico Star Tracker (APST) is designed based on the limitations of nanosatellites and estimated to provide pointing knowledge in arcsecond. The APST is developed using fully COTS components because its affordable, and less development time. A theoretical model is developed to estimate the performance of the COTS components (image sensor, lens, and baffle) used in the APST. Using this model, its possible to validate if the components meet the requirements of the star tracker. But COTS component decreases the overall performance due to the errors in image sensor noise, lens distortion, and aberration etc. In APST, the lens distortion and inaccurate centroiding are the dominant error sources. The radial lens distortion causes an error in angular distance measurement, which leads misidentifying or identification of stars and high processing time. This leads to functional failure of APST. To overcome this, the relative star selection method is developed which selects the stars based on the angular distance information. Based on the fact that star pair with low angular distance has minimum measurement error, the relative star selection selects the four stars with low measurement error. Its compared with conventional bright star selection method, whereas stars are selected based on brightness. The relative selection algorithm is tested with 75-star constellation in star simulator and it has delivered 100% success rate and accuracy of 71 arcseconds in boresight. Whereas the conventional bright star selection delivered low success rate of 28% because the star pairs are not selected based on angular distance separation. Hence the relative star selection algorithm is efficient for APST.
Language
English
URI
https://hdl.handle.net/10371/140558
Files in This Item:
Appears in Collections:
College of Engineering/Engineering Practice School (공과대학/대학원)Dept. of Mechanical Aerospace Engineering (기계항공공학부)Theses (Ph.D. / Sc.D._기계항공공학부)
  • mendeley

Items in S-Space are protected by copyright, with all rights reserved, unless otherwise indicated.

Browse