空间高分辨率对地遥感在民生及军事领域应用愈加广泛。随着成像分辨率提升，海量图像数据存储及传输压力逐步凸显出来，成像探测器及模数转换器件的性能限制也成为技术瓶颈。我国正逐步开展深空探测计划，其低传输带宽为图像数据传输带来了技术难题，同时还面临成像系统体积、质量及功耗等严苛限制。因此寻求一种新型图像数据采集及处理方法成为高分辨率遥感成像领域的迫切需要。压缩感知理论引入有望从根本上为上述问题提供解决方案，其中在探测器光电转换过程中实施压缩编码感知具备诸多优势，是解决上述空间遥感和深空探测面临问题的合理切入点。本项目提出了基于TDI-CCD连续电荷转移模式的新型超分辨率空间光学遥感计算成像实现方法的研究设想，作为解决目前空间遥感成像领域所面临问题的有效手段，其有望成为下一代高分辨率对地遥感以及深空探测领域中成像系统工作方式的补充，也将是未来高性价比光学成像载荷的实现途径之一，具有重要工程应用价值。

High-resolution space remote sensing is increasingly used in people's livelihood and military fields. With the improvement of imaging resolution, the storage and transmission pressure of massive image data has gradually emerged, and the performance limitations of imaging detectors and analog-to-digital conversion devices have also become technical bottlenecks. Our country is gradually carrying out deep space exploration program. Its low transmission bandwidth has brought technical difficulties for image data transmission, and it also faces severe restrictions such as the size, quality and power consumption of the imaging system. Therefore, searching for a new image data acquisition and processing method has become an urgent need in the field of high-resolution remote sensing imaging. The introduction of compressed sensing theory is expected to provide a solution to the above problems fundamentally. The implementation of compressed coding sensing in the photoelectric conversion process of detectors has many advantages, which is a reasonable entry point to solve the problems faced by the above-mentioned space remote sensing and deep space exploration. In this project, an innovative super-resolution space remote sensing computational imaging implementation method based on TDI-CCD continuous charge transfer mode is proposed. As an effective means to solve the current problems in the field of space remote sensing, it is expected to become a supplement to the working mode of imaging system in the next generation of high-resolution remote sensing and deep space exploration, and it will also be one of the ways to realize the cost-effective imaging payload in the future, which has important engineering application value.