The on-orbit processing technology of remote sensing satellites stands as a pivotal component driving the achieve-ment of real-time intelligent services in remote sensing technology.In response to the challenges posed by limited on-orbit re-sources and the growing demands for real-time data processing and information extraction,this paper initially establishes a task-driven framework for on-orbit processing of satellite remote sensing data.The framework places mission requirements at the core and collaborates with space and ground-based resources to establish a comprehensive on-orbit processing system cen-tered around regions of interest(ROIs).In addition,this paper addresses the diverse needs of different task levels and applica-tion scenarios by presenting on-orbit processing modes;the basic model driven by location information and the intelligent modes driven by target or scene content and change events.Finally,this paper delves into the critical algorithms necessary for adapting to the resource-constrained on-board environment.Using the on-orbit processing applications(APPs)on the Luojia-301 satellite,the performance of these algorithms was verified.Under the framework of task-driven processing and satellite-ground coordination,the Luojia-3 01 satellite successfully achieved high-precision on-orbit geo-positioning,rapid generation of multi-type image products,real-time extraction of information from both static and dynamic targets,and high-rate,near real-time compression of static and dynamic images.The on-orbit processing significantly enhances the efficiency of traditional ground-based processing and effectively supports subsequent real-time intelligent services in satellite remote sensing.
维普
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