  This paper introduces a novel method using chaser spacecraft image processing
and Convolutional Neural Networks (CNNs) to detect structural markers on the
European Space Agency's (ESA) Environmental Satellite (ENVISAT) for safe
de-orbiting. Advanced image pre-processing techniques, including noise addition
and blurring, are employed to improve marker detection accuracy and robustness.
Initial results show promising potential for autonomous space debris removal,
supporting proactive strategies for space sustainability. The effectiveness of
our approach suggests that our estimation method could significantly enhance
the safety and efficiency of debris removal operations by implementing more
robust and autonomous systems in actual space missions.
