By Topic

Small field-of-view star identification using Bayesian decision theory

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Clouse, D. ; Jet Propulsion Lab., California Univ., San Diego, La Jolla, CA, USA ; Padgett, C.W.

We describe a simple autonomous star identification algorithm which is effective using a narrow field of view (FOV) (2 deg), making the use of a science camera for star identification feasible. This work extends that of Padgett and Kreutz-Delgado (1997) by setting decision thresholds using Bayesian decision theory. Our simulations show that when positional accuracy of imaged stars is 0.5 pixel (standard deviation) and the apparent brightness deviates by 0.8 unit stellar magnitude, the algorithm correctly identifies 96.0% of the sensor orientations, with less than a 0.3% rate of false positives

Published in:

Aerospace and Electronic Systems, IEEE Transactions on  (Volume:36 ,  Issue: 3 )