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REN Zhipeng, YU Tingting, LI Shaoyang, WANG Yuhan. Coupled Ionosphere-Thermosphere Model for Spaceborne Intelligent Platforms (in Chinese). Chinese Journal of Space Science, 2026, 46(5): 1-8 doi: 10.11728/cjss2026.05.2025-0239
Citation: REN Zhipeng, YU Tingting, LI Shaoyang, WANG Yuhan. Coupled Ionosphere-Thermosphere Model for Spaceborne Intelligent Platforms (in Chinese). Chinese Journal of Space Science, 2026, 46(5): 1-8 doi: 10.11728/cjss2026.05.2025-0239

Coupled Ionosphere-Thermosphere Model for Spaceborne Intelligent Platforms

doi: 10.11728/cjss2026.05.2025-0239 cstr: 32142.14.cjss.2025-0239
  • Received Date: 2025-12-29
  • Rev Recd Date: 2026-05-06
  • Available Online: 2026-05-08
  • With the development of space systems toward autonomy and intelligence, the traditional “space-sensed, ground-computed” model for space-environment support can no longer meet the needs of real-time response and autonomous decision-making. Aiming at the urgent demand of satellite platforms for real-time space-environment information, this study carries out an onboard-oriented reconstruction of the autonomous global ionosphere-thermosphere coupled model GCITEM-IGGCAS. Focusing on three major challenges encountered during in-orbit operation-system adaptability, computational efficiency, and real-time performance-this work implements several key upgrades, including adaptation and robustness enhancement of the operating environment, optimization of computational efficiency, and the construction of standardized data interfaces. Based on preserving the original physical core, the upgraded model significantly improves operational robustness, computational efficiency, and dynamic responsiveness across diverse onboard platforms. Simulation results demonstrate that the model can stably output key environmental parameters, such as thermospheric neutral density and ionospheric total electron content, whose spatial distributions are physically consistent. This indicates strong potential for providing real-time environmental inputs for tasks such as autonomous orbit management and enhanced communication and navigation. The study offers a feasible pathway for transforming high-end scientific models into intelligent onboard modules, and is of great significance for advancing “space-sensed, space-computed” capabilities.

     

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