Version 1
: Received: 22 October 2024 / Approved: 22 October 2024 / Online: 22 October 2024 (11:04:43 CEST)
How to cite:
Wang, G.; Wan, G.; Su, Z.; Wang, Y.; Jia, Y.; Li, G.; Liang, S. High-performance On-orbit Intelligent Computing and Real-time Services for Remote Sensing Satellites Based on Space Large-scale Computing Power. Preprints2024, 2024101714. https://doi.org/10.20944/preprints202410.1714.v1
Wang, G.; Wan, G.; Su, Z.; Wang, Y.; Jia, Y.; Li, G.; Liang, S. High-performance On-orbit Intelligent Computing and Real-time Services for Remote Sensing Satellites Based on Space Large-scale Computing Power. Preprints 2024, 2024101714. https://doi.org/10.20944/preprints202410.1714.v1
Wang, G.; Wan, G.; Su, Z.; Wang, Y.; Jia, Y.; Li, G.; Liang, S. High-performance On-orbit Intelligent Computing and Real-time Services for Remote Sensing Satellites Based on Space Large-scale Computing Power. Preprints2024, 2024101714. https://doi.org/10.20944/preprints202410.1714.v1
APA Style
Wang, G., Wan, G., Su, Z., Wang, Y., Jia, Y., Li, G., & Liang, S. (2024). High-performance On-orbit Intelligent Computing and Real-time Services for Remote Sensing Satellites Based on Space Large-scale Computing Power. Preprints. https://doi.org/10.20944/preprints202410.1714.v1
Chicago/Turabian Style
Wang, G., Gong Li and Shi Liang. 2024 "High-performance On-orbit Intelligent Computing and Real-time Services for Remote Sensing Satellites Based on Space Large-scale Computing Power" Preprints. https://doi.org/10.20944/preprints202410.1714.v1
Abstract
The rapid advancement of Earth observation systems and satellite networks driven by commercial space has led to a significant increase in the number of remote sensing satellites, thereby establishing the groundwork for all-weather, continuous cluster collaborative observation. Following anti-irradiation hardening measures, low-cost commercial off-the-shelf (COTS) devices are effectively operated within intricate space environments, leading to substantial enhancements in on-orbit computing capabilities of individual satellites. Leveraging the on-board distributed processing framework, it fully utilizes wide-area scattered space computing resources and automatically establishes a network of neighboring satellites through inter-satellite communication links to construct a spatially distributed and computationally cooperative space cloud computing environment. This enables the sharing of space computing resources and facilitates satellite-based mission coordination, reducing reliance on ground-based remote sensing satellite services while enhancing the response efficiency of remote sensing application services. The present paper pro-vides a comprehensive review of the current development status, existing challenges, and problems faced by space-based remote sensing on-orbit processing platforms and on-board intelligent processing algorithms, starting from the immediate application requirements of remote sensing satellite in-orbit processing. In view of the anticipated surge in large-scale computing resources in space, a distributed remote sensing satellite data processing architecture based on large-scale on-board computing power is constructed, and the architecture is designed in detail from the aspects of physical architecture, software architecture, workflow and key technologies. Finally, three real-time service scenarios that align with the construction content of an ultra-low orbit satellite constellation and 6G technology have been designed to provide solutions and references for subsequent development of space-based intelligent remote sensing constellations.
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
