|
|
|
|
LEADER |
01565 am a22001933u 4500 |
001 |
125244 |
042 |
|
|
|a dc
|
100 |
1 |
0 |
|a Leake, Carl
|e author
|
100 |
1 |
0 |
|a Massachusetts Institute of Technology. Department of Aeronautics and Astronautics
|e contributor
|
700 |
1 |
0 |
|a Arnas Martinez, David
|e author
|
700 |
1 |
0 |
|a Mortari, Daniele
|e author
|
245 |
0 |
0 |
|a Non-Dimensional Star-Identification
|
260 |
|
|
|b Multidisciplinary Digital Publishing Institute,
|c 2020-05-14T19:23:23Z.
|
856 |
|
|
|z Get fulltext
|u https://hdl.handle.net/1721.1/125244
|
520 |
|
|
|a This study introduces a new “Non-Dimensional” star identification algorithm to reliably identify the stars observed by a wide field-of-view star tracker when the focal length and optical axis offset values are known with poor accuracy. This algorithm is particularly suited to complement nominal lost-in-space algorithms, which may identify stars incorrectly when the focal length and/or optical axis offset deviate from their nominal operational ranges. These deviations may be caused, for example, by launch vibrations or thermal variations in orbit. The algorithm performance is compared in terms of accuracy, speed, and robustness to the Pyramid algorithm. These comparisons highlight the clear advantages that a combined approach of these methodologies provides. Keywords: star identification; non-dimensional; Pyramid; n-dimensional k-vector
|
520 |
|
|
|a NASA Space Technology Research Fellowship, Leake [NSTRF 2019]Grant #: 80NSSC19K1152
|
520 |
|
|
|a NASA Grant #: 80NSSC19P1369
|
655 |
7 |
|
|a Article
|
773 |
|
|
|t Sensors
|