Title

Recursive Filtering of Star Tracker Data

Abstract

Star trackers typically obtain attitude information about a vehicle by imaging a portion of the sky and matching the observed stars to those in a known star catalog. The light gathered from each star is typically assumed to be Gaussian-distributed in the image plane, such that the measured direction to each star is the mean of the Gaussian. The measured direction to the star, along with its known direction in some reference frame, is then used to determine the attitude and its associated uncertainty of the vehicle at the epoch in which the image was taken. This data is then processed by an attitude filter to fuse the new information with a prior estimate. This paper investigates the application of the multiplicative extended Kalman filter (MEKF) filter for attitude determination using star tracker measurements. Two MEKFs are considered: one processes the outputs of the star tracker assuming that a quaternion measurement is returned, and the other directly processes the measured pixel locations. It is found that both MEKFs perform nearly identically and provide a statistically consistent solution with a Monte Carlo analysis.

Meeting Name

AIAA/AAS Astrodynamics Specialist Conference (2016: Sep. 13-16, Long Beach, CA)

Department(s)

Mechanical and Aerospace Engineering

Keywords and Phrases

Astrophysics; Stars; Attitude determination; Gaussian distributed; Monte carlo analysis; Multiplicative extended kalman filters; Pixel location; Prior estimates; Recursive filtering; Reference frame; Star trackers

International Standard Book Number (ISBN)

9781624104459

Document Type

Article - Conference proceedings

Document Version

Citation

File Type

text

Language(s)

English

Rights

© 2016 American Institute of Aeronautics and Astronautics (AIAA), All rights reserved.

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