Genetic Algorithm for Space Debris and Space Objects Attitude Motion Reconstruction Through Optical Measurements

Space debris has recently become a major problem in the planning and execution of space missions. Due to the recent widespread placement of satellite mega- constellations in Low Earth Orbits (LEO), where most of the catalogued debris is located, the need to monitor such uncontrolled objects and maintain an up-to-date catalogue has increased. Moreover, estimating the attitude motion of a space object is fundamental to improving methods for orbit determination and supporting eventual Active Debris Removal (ADR) missions. The Sapienza Space System and Space Surveillance Laboratory (S5Lab), whose researchers have years of experience in space debris detection, operates an extensive observation network that can exploit different observation strategies. This paper illustrates the reconstruction of an object’s attitude motion from its light curve, which can be extracted using scientific Complementary Metal-Oxide Semiconductor (sCMOS) sensors installed on high-slew rate telescopes. The method is based on a comparison between the object's actual light curve and a synthetic curve created by changing the initial conditions for the attitude motion, considering the observer's motion, the Sun’s position, the object’s position and its 3D model. A genetic algorithm is used to create multiple synthetic light curves by varying the initial conditions for the attitude motion until one of them matches the observed one. In addition to extracting the light curves and reconstructing the attitude, observational strategies for acquiring light curves are discussed. Finally, the results of the investigation of potentially hazardous debris are presented.