RSO Detection

RSO detection focuses on automatically identifying resident space objects (RSOs), such as satellites and debris, within astronomical or space-based imagery. Current research heavily utilizes deep learning, particularly convolutional neural networks (CNNs), often combined with other techniques like recurrent neural networks (RNNs) or gradient boosting, to detect streak-like features characteristic of moving objects. This work is crucial for improving space situational awareness, enabling more efficient collision avoidance, and facilitating more accurate orbital determination, ultimately enhancing space safety and scientific understanding of the space environment.