Non-dimensional Star-Identification
This addresses a specific issue for spacecraft navigation systems where inaccurate sensor parameters can lead to incorrect star identification, though it appears incremental as it builds on and complements existing lost-in-space algorithms.
The paper tackles the problem of star identification in star trackers when focal length and optical axis offset are inaccurately known, introducing a non-dimensional algorithm that complements existing methods to improve reliability under deviations like launch vibrations or thermal changes, with results showing clear advantages in accuracy, speed, and robustness compared to the Pyramid algorithm.
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.