针对高分辨率宽覆盖遥感影像数据量大，星上数据存储、处理与传输能力受限的问题，研究任务驱动的遥感数据星地协同处理机制、遥感数据星地协同智能实时处理方法、星上通用信息处理平台架构及构建技术，研制任务驱动的遥感数据星地协同处理原型样机并进行实验验证，突破任务驱动的遥感数据星地协同处理机制和基于区域分类和稀疏表征的星上数据智能压缩机理关键科学问题，实现星地数据获取资源、计算资源、存储资源、传输资源、接收资源、处理算法高效协同，为空间信息在轨获取、处理与实时应用提供关键理论和技术支撑，也为空间信息网络中高时效数据处理奠定理论和技术基础。

The high resolution satellite with wide coverage has big volume of data, which brings great pressure and challenge to the onboard data storage, processing and transmission capacity. This project focused on three aspects of research content, including (1) remote sensing data onboard/ground collaborative processing mechanism by task driven approach, (2) remote sensing data intelligent real-time onboard-ground collaborative processing method and (3) general onboard information processing platform architecture and building technology. And on this basis we develop the prototype of task-driven onboard/ground collaborative processing for remote sensing data and conduct validation experiments. The objective of the project is to break through two key scientific problems, which are task drive mechanism of remote sensing data onboard/ground cooperative processing and remote sensing data intelligent onboard compression mechanism based on coarse classification and sparse representation, and realize efficient synergy of data acquisition resources, computing resources, storage resources, transmission resources and processing algorithm resources. The research achievement of this project can provide the key theory and technology support for space information onboard acquisition, processing and real-time applications and lay the theoretical and methodological foundation for real-time data processing in Space Information Network.