Optimization Techniques for Feature Detection of Orbital Debris

Kurzfassung

Space debris is exponentially increasing and becoming a pressing concern, as demonstrated by the recent malfunctioning of the European Space Agency’s Envisat and the Japanese Space Agency’s Hitomi. In this study, we propose a novel vision-based feature detection technique for the next generation of satellites to perform autonomous obstacle avoidance. The study evaluates the strength and shortcomings of thermal and visible imaging to detect an approaching subject. For this purpose, the subject was imaged in various lighting conditions and contrasts of temperature relative to the ambient temperature. Preliminary results suggested that thermal imaging at distances greater than 2m offers a higher detection accuracy in contrast to using visible imaging. However, outdoors test proved that both images offered similar poor detection readings. Fluctuations of wind and turbulence may have contributed to the low performance of the thermal images, as well as extreme illuminations respectively impacted the detection results of the visible images which were observed.