Zhaokui WANG, Chunwu LIU, Yingkai CAI. Technologies and Perspectives for Space-based Cooperative Perception of Space Targets[J]. AEROSPACE SHANGHAI, 2024, 41(6): 1

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- AEROSPACE SHANGHAI
- Vol. 41, Issue 6, 1 (2024)
![The ADRIOS of ESA[11-12]](/richHtml/shht/2024/41/6/1/A48B10F0-BB14-4c4b-8517-3E321ADA10C2-F001c.jpg)
![Diagram of the EAGLE[13-14]](/richHtml/shht/2024/41/6/1/A48B10F0-BB14-4c4b-8517-3E321ADA10C2-F002c.jpg)
![The GSSAP satellite of United States Air Force[15-17]](/Images/icon/loading.gif)
![Conceptual figure of the S5 satellite[18-19]](/Images/icon/loading.gif)
![The Silentbarker satellite[20-21]](/Images/icon/loading.gif)
![Conceptual diagram of the Tetra satellite[22-24]](/Images/icon/loading.gif)

Fig. 7. SBO camera payloads on a board space-based observation satellite
![Geometric model of space-based radar detection[33]](/Images/icon/loading.gif)
Fig. 8. Geometric model of space-based radar detection[33]
![Multi-sensor fusion images[44]](/Images/icon/loading.gif)
Fig. 9. Multi-sensor fusion images[44]
![Data layer fusion[45]](/Images/icon/loading.gif)
Fig. 10. Data layer fusion[45]
![Feature layer fusion[45]](/Images/icon/loading.gif)
Fig. 11. Feature layer fusion[45]

Fig. 12. Decision layer fusion

Fig. 13. Collaborative close-in observation by multiple spacecrafts
![Strategies for applying deep reinforcement learning algorithms to spacecraft motion planning[56]](/Images/icon/loading.gif)
Fig. 14. Strategies for applying deep reinforcement learning algorithms to spacecraft motion planning[56]
![Architecture of the position-attitude dual-channel feature fusion network[58]](/Images/icon/loading.gif)
Fig. 15. Architecture of the position-attitude dual-channel feature fusion network[58]

Fig. 16. Structure of the CNN
![Principle of the GAN[67]](/Images/icon/loading.gif)
Fig. 17. Principle of the GAN[67]

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