Attitude inversion of space debris based on the laboratory-tested photometry dataset

Abstract

The attitude of space debris holds significant implications for active debris removal and collision warnings. This study constructs a comprehensive photometry dataset for the target, utilizing angle transformation relationships and drawing upon the CZ-4C photometric data tested in the laboratory. The photometry in the dataset with noise and translation simulates the telescope observed one. We use the genetic algorithm to search for attitude parameters of the photometry that matches the simulated photometry in the dataset under the constraint of attitude angle rules. The derived and preset values of attitude parameters exhibit a strong alignment, applicable to light curves with an amplitude of about 2.5 magnitudes and noise levels up to 1.0 magnitudes. This suggests that the algorithm’s accuracy is validated against the preset values, demonstrating its robust resistance to noise. Furthermore, the algorithm proposed in this study for deriving attitude from photometry requires a small amount of photometry data. This study provides a promising algorithm for future attitude analyses from telescope-observed photometry.