DRL-based link planning algorithm for mega constellation satellite and TT&C

doi:10.16708/j.cnki.1000-758X.2023.0069

Abstract

Abstract: Aiming at the planning of satellite and TT&C links in mega constellations，an intelligent planning and scheduling algorithm based on deep reinforcement learning was proposed.The resource competition and connection relationship between satellite and TT&C station were considered，the environment state was designed，and the allocation scheme of satellite to TT&C station was generated by sensing the satellite state and combining the action selection strategy.Iterative optimization of the strategy was performed according to the feedback reward value.The proposed algorithm was applied to the satellite and TT&C link planning task of the mega constellation system.The simulation results show that the proposed intelligent algorithm can improve the antenna utilization rate of TT&C station to more than 98%，and can effectively reduce the frequency of antenna switching.The trained model can quickly generate the satellite and TT&C link planning scheme within 30s according to the satellitebased visual window at the future time.

Key words: , mega constellations, satellite and TT&, C links, deep reinforcement learning, antenna utilization, switching times

XI Chao, YANG Bo, WANG Jirong, LI Gong, ZHU Ruijie, YANG Xiao. DRL-based link planning algorithm for mega constellation satellite and TT&C[J]. Chinese Space Science and Technology, 2023, 43(5): 65-70.

0
/ / Recommend

Add to citation manager EndNote|Reference Manager|ProCite|BibTeX|RefWorks

URL: http://journal26.magtechjournal.com/kjkxjs/EN/10.16708/j.cnki.1000-758X.2023.0069

http://journal26.magtechjournal.com/kjkxjs/EN/Y2023/V43/I5/65

[1]	ZOU Xin, PENG Jing, MIAO Yuanming. Research and prospect of scientific exploration for Jovian system [J]. Chinese Space Science and Technology, 2023, 43(6): 1-10.
[2]	SUN Jingyun, ZHANG Guoting, LIU Zhen, GUO Jie, WANG Jin. Constellation coverage performance analysis based on Markov-ADC model [J]. Chinese Space Science and Technology, 2023, 43(5): 24-34.
[3]	YUN Chaoming, HU Min, RUAN Yongjing, XUE Wen. Internal anti-collision safety analysis of LEO largescale satellite constellation [J]. Chinese Space Science and Technology, 2023, 43(5): 35-45.
[4]	ZHU Chao, ZHANG Wenming, HU Chengwei, TANG Zixin, LIANG Changchun, KONG Xu, LI Delun, WANG Youyu, ZENG Lei, ZHANG Xinrui. Maintenance system design and verification for space station manipulator end-effector [J]. Chinese Space Science and Technology, 2023, 43(5): 79-86.
[5]	MIAO Jun, TU Xinying, YIN Jianfeng, PENG Jing, LI Haijin, CHEN Ziyun. Hypercube satellite formation control based on ADDPG strategy [J]. Chinese Space Science and Technology, 2023, 43(4): 24-34.
[6]	DAI Wei, ZHANG Zhongyuan, LI Guangyu, HAN Wei. Grid convergence analysis for numerical simulation of propellant reposition process in vane-type surface tension tank [J]. Chinese Space Science and Technology, 2023, 43(4): 85-92.
[7]	ZHANG Yasheng, JIA Lu, YU Jinlong, LIANG Shuang. LEO constellation configuration design method with constant trajectory of subsatellite points [J]. Chinese Space Science and Technology, 2023, 43(3): 116-122.
[8]	WANG Shuai, LIU Xiangyang, ZHAO Zijing, GUO Haoran, GENG Jinyue, SHEN Yan, WANG Ningfei. Probe diagnosis of plume of micro-cathode arc thruster [J]. Chinese Space Science and Technology, 2023, 43(2): 47-54.
[9]	LYU Jiahang, LI Qian, HU Dingkun, LUO Haotian, ZOU Xinyue. Mechanical model for lunar surface sampling based on modular theory [J]. Chinese Space Science and Technology, 2023, 43(2): 63-72.
[10]	LI Shenglin, LIU Bo, ZHAO Ben, LI Dacheng, WANG Yuheng, GUO Fengyun. Landsat 8 land surface temperature product validation and analysis [J]. Chinese Space Science and Technology, 2023, 43(2): 174-182.
[11]	LIU Shiyuan, Zhang Ce, YIN Zhao, YANG Jinlu, YAO Wei, YANG Mengfei. Perspective of extraterrestrial carbon dioxide conversion and utilization technologies [J]. Chinese Space Science and Technology, 2022, 42(6): 1-11.
[12]	ZHANG Chengyue, QUAN Ronghui, ZHANG Haicheng. Dielectric surface charging potential inversion method based on BP neural network [J]. Chinese Space Science and Technology, 2022, 42(6): 134-139.
[13]	XUE Wen, HU Min, RUAN Yongjing, YUN Chaoming, SUN Tianyu. Analysis of the first stage deployment of Starlink constellation based on TLE [J]. Chinese Space Science and Technology, 2022, 42(5): 24-33.
[14]	YU Bo, XU Yanan, KANG Xiaolu. Changing rules of plume pattern and thermal characteristics in discharge modes of hollow cathodes [J]. Chinese Space Science and Technology, 2022, 42(5): 65-77.
[15]	ZHENG Kai, XIANG Yanchao, RAO Wei, ZHANG Bingqiang, XUE Shuyan, DAI Chenghao, ZHANG Dong, WANG Yuying. Design and verification of thermal control system for Tianwen-1 Mars entry capsule [J]. Chinese Space Science and Technology, 2022, 42(5): 108-116.

DRL-based link planning algorithm for mega constellation satellite and TT&C

PDF (PC)

Knowledge

Abstract

Cite this article

share this article

References

Related Articles 15

Recommended Articles

Metrics

Comments