Self-organizing guide star selection algorithm for star trackers: Thinning method Conference Paper

abstract

• In this study, a new self-organizing guide star selection algorithm is presented, which is a crucial part of an advanced star tracker design since the performance and reliability of star pattern recognition and attitude determination depend on the guide star selection. The problem is to minimize the total number of guide stars while ensuring at least n guide stars be measured inside a specified field of view (FOV), in every possible boresight direction. The process depends implicitly upon redundant measured stars, especially in regions of high star density. Obviously this selection process is constrained such that the stars brighter than some sensor-dictated magnitude threshold are selected for the guide star catalog. This extremely high dimensional optimization problem is impossible to solve rigorously in finite time. In this study, a heuristic approach is used to obtain the near minimum number of guide stars satisfying above constraints. The algorithm is demonstrated by generating mission catalogs for a star tracker with an 8degreesx8degrees squared FOV.

name of conference

• 2002 IEEE AEROSPACE CONFERENCE PROCEEDINGS, VOLS 1-7

authors

• Junkins, John

author list (cited authors)

• IEEE, .., IEEE, .., Kim, H. Y., & Junkins, J. L.

complete list of authors

• Kim, HY||Junkins, JL

publication date

• 2002

published in

• IEEE Aerospace Conference Proceedings  Journal

International Standard Book Number (ISBN) 10

• 0-7803-7231-X

start page

• 2275

end page

• 2283

volume

• IEEE Aerospace Conference