This paper deals with a fast and efficient Lost in Space algorithm for stars pattern recognition in harsh environments using star trackers. Typically, the attitude determination system for CubeSats is based on low accuracy instruments such as sun sensors and magnetometers. However, it is expected that next CubeSat generations will require more accurate attitude estimations provided by stars sensors. False spikes represent the major issue in star identification since star trackers for CubeSat generally have low radiation shielding. The proposed technique is based on the Multi-Poles Algorithm approach. Stars are identified in two phases: 1) the acceptance phase, to yield a set of stars, and 2) the check phase, to avoid erroneous identification. The identification feature is the angular distance between two stars while stars magnitudes are used as a filtering feature to improve the searching strategy. Tests have shown that the algorithm guarantees a reliable identification of stars up to 80 artifacts per image.
Efficient star identification algorithm for nanosatellites in harsh environment / Schiattarella, Vincenzo; Spiller, Dario; Curti, Fabio. - STAMPA. - 163:(2018), pp. 287-306. (Intervento presentato al convegno 4th IAA Conference on university satellite missions and cubesat workshop tenutosi a Roma; Italy).
Efficient star identification algorithm for nanosatellites in harsh environment
Vincenzo Schiattarella
;dario Spiller;Fabio Curti
2018
Abstract
This paper deals with a fast and efficient Lost in Space algorithm for stars pattern recognition in harsh environments using star trackers. Typically, the attitude determination system for CubeSats is based on low accuracy instruments such as sun sensors and magnetometers. However, it is expected that next CubeSat generations will require more accurate attitude estimations provided by stars sensors. False spikes represent the major issue in star identification since star trackers for CubeSat generally have low radiation shielding. The proposed technique is based on the Multi-Poles Algorithm approach. Stars are identified in two phases: 1) the acceptance phase, to yield a set of stars, and 2) the check phase, to avoid erroneous identification. The identification feature is the angular distance between two stars while stars magnitudes are used as a filtering feature to improve the searching strategy. Tests have shown that the algorithm guarantees a reliable identification of stars up to 80 artifacts per image.File | Dimensione | Formato | |
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