• AEROSPACE SHANGHAI
  • Vol. 41, Issue 6, 1 (2024)
Zhaokui WANG*, Chunwu LIU, and Yingkai CAI
Author Affiliations
  • School of Aerospace Engineering,Tsinghua University,Beijing100084,China
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    DOI: 10.19328/j.cnki.2096-8655.2024.06.001 Cite this Article
    Zhaokui WANG, Chunwu LIU, Yingkai CAI. Technologies and Perspectives for Space-based Cooperative Perception of Space Targets[J]. AEROSPACE SHANGHAI, 2024, 41(6): 1 Copy Citation Text show less
    The ADRIOS of ESA[11-12]
    Fig. 1. The ADRIOS of ESA11-12
    Diagram of the EAGLE[13-14]
    Fig. 2. Diagram of the EAGLE13-14
    The GSSAP satellite of United States Air Force[15-17]
    Fig. 3. The GSSAP satellite of United States Air Force15-17
    Conceptual figure of the S5 satellite[18-19]
    Fig. 4. Conceptual figure of the S5 satellite18-19
    The Silentbarker satellite[20-21]
    Fig. 5. The Silentbarker satellite20-21
    Conceptual diagram of the Tetra satellite[22-24]
    Fig. 6. Conceptual diagram of the Tetra satellite22-24
    SBO camera payloads on a board space-based observation satellite
    Fig. 7. SBO camera payloads on a board space-based observation satellite
    Geometric model of space-based radar detection[33]
    Fig. 8. Geometric model of space-based radar detection33
    Multi-sensor fusion images[44]
    Fig. 9. Multi-sensor fusion images44
    Data layer fusion[45]
    Fig. 10. Data layer fusion45
    Feature layer fusion[45]
    Fig. 11. Feature layer fusion45
    Decision layer fusion
    Fig. 12. Decision layer fusion
    Collaborative close-in observation by multiple spacecrafts
    Fig. 13. Collaborative close-in observation by multiple spacecrafts
    Strategies for applying deep reinforcement learning algorithms to spacecraft motion planning[56]
    Fig. 14. Strategies for applying deep reinforcement learning algorithms to spacecraft motion planning56
    Architecture of the position-attitude dual-channel feature fusion network[58]
    Fig. 15. Architecture of the position-attitude dual-channel feature fusion network58
    Structure of the CNN
    Fig. 16. Structure of the CNN
    Principle of the GAN[67]
    Fig. 17. Principle of the GAN67