## 1 Introduction  
With continuous space activities, space situational awareness (SSA) has become a key research project in nations with space technologies, which can persistently track the non-space cooperation targets persistently by active laser detecting system in Earth stations [1, 2]. In the space environments of low Earth orbit, the existing technologies for orbital correction in practice can effectively compensate the cumulative long-duration interferences on satellites from space perturbation forces, but the sudden disturbance caused by perturbation force will reduce the tracking precision of ground tracking systems [3, 4]. Therefore, research on high-bandwidth instantaneous orbit perception and tracking correction techniques for the random orbital deviations of in-orbit satellites has become a central focus in SSA. In order to improve the SSA performance of detecting systems, the current practice in astronomical observation institutions is to increase the optical antenna aperture of satellite-ground laser-detecting systems, which improves the echo detecting power for satellite targets. For example, the McDonald Observatory in Texas, USA, employed a telescope with an optical aperture of 0.76 m [5]; the Zimmerwald Observatory in Switzerland constructed a telescope with an optical aperture of 1.2 m [6]; the optical ground station of the European Space Agency in Tenerife, Spain, was equipped with a telescope that has an optical aperture of 1 m [7]; the Zi Jinshan Observatory in Shanghai, China, is equipped with a telescope whose optical aperture is 1.5 m [8]. Changchun Observatory of the National Astronomical Observatories uses a telescope with an optical aperture of 1 m [9]. However, referring to the theories of classical applied optics, when simply increasing the aperture of the optical antenna, the focal length will increase in the optical systems, thereby reducing the detecting field of view. Therefore, while improving the aperture of the optical antenna, imaging detectors with larger imaging surface size (such as CCD CMOS) should be adopted to maintain the range of the detecting field of view [10]. Benefiting from the development of semiconductor imaging detectors, imaging detector products with large image surface sizes have been gradually enriched. The method that realizes high robust target sensing and tracking by combining the large-aperture optical antenna with the large-image surface size imaging detector has become a development trend to improve the SSA capability of on-orbit targets [11]. However, further increasing the size of imaging detectors results in a nonlinear growth of tracking image data; hence, the image data processing capability of the existing tracking systems cannot meet the real-time technical requirements. In recent years, methods achieving highly robust target tracking by deep learning on spatiotemporal context information have been proposed [12; 13; 14]. The Convolutional Long Short-Term Memory (ConvLSTM) network combined the spatial awareness of convolutional neural networks with the temporal memory characteristics of LSTM, effectively modeling dynamic changes in image sequences. It was particularly suitable for spatiotemporal data modeling tasks [15]. However, its complex architecture and large number of parameters resulted in high training costs, and it suffered from the vanishing gradient problem when processing long sequences.The 3D Convolutional Neural Network (3D-CNN) captured variations across both temporal and spatial dimensions using three-dimensional convolution, offering a compact structure and high inference efficiency [16]. It was well suited for short-term motion prediction tasks. Nonetheless, its inherent fixed time window limited its adaptability to variable-length sequence prediction, and its modeling capacity was constrained in long-term prediction tasks. U-Net Recurrent Prediction integrated the classic encoder-decoder structure of U-Net with a temporal recurrence mechanism to achieve target prediction [17].