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Aiming at the target satellite detection problems that need to be solved in space on-orbit services such as satellite component maintenance and replacement, fuel refueling, and recycling of abandoned satellites, an improved instance segmentation network model Ring-Engine-Mask R-CNN is proposed on the basis of Mask R-CNN by improve the structure of its backbone network and reducing channels of classification, regression, Mask branch. The network uses physical model images and simulation images generated by 3ds Max to establish a dedicated dataset, and presents a satellite target detection method based on deep learning. The experimental results show that this method can complete the detection and segmentation task of the two target parts of the satellite marman ring and the apogee engine nozzle better. Compared with the traditional network model, it has a smaller model volume. Meanwhile, it has a higher detection accuracy and faster speed.