Multi-Ground Station Collaborative Measurement and Control Technology for Giant Constellation System
Measurement and control technology is the key technology to ensure the effi cient operation, maintenance and management of the constellation system.In recent years, with the continuous expansion of the constellation scale, mega-constellation system has gradually formed, which makes the demand for co...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | zho |
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Post&Telecom Press Co.,LTD
2023-03-01
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| Series: | 天地一体化信息网络 |
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| Online Access: | http://www.j-sigin.com.cn/zh/article/doi/10.11959/j.issn.2096-8930.2023001/ |
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| _version_ | 1841533884253077504 |
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| author | Yang LIU Di ZHOU Min SHENG Jiandong LI Shiguang HAO Xiaotian ZHENG |
| author_facet | Yang LIU Di ZHOU Min SHENG Jiandong LI Shiguang HAO Xiaotian ZHENG |
| author_sort | Yang LIU |
| collection | DOAJ |
| description | Measurement and control technology is the key technology to ensure the effi cient operation, maintenance and management of the constellation system.In recent years, with the continuous expansion of the constellation scale, mega-constellation system has gradually formed, which makes the demand for constellation measurement and control show an explosive growth, which puts forward new requirements for the completion of the constellation system measurement and control tasks.Firstly, the constraints of the megaconstellation system measurement and control tasks and the equipment constraints of the ground measurement and control station were analyzed, and the problem modeling was given; Secondly, an interaction method of the ground station agent based on the learning planning segment was proposed, by introduced the constraint penalty operator and the multi-ground station joint the penalty operator was designed to optimized the objective function.Finally, a multi-ground station Agent reinforcement learning algorithm was proposed to solved the multi-ground station cooperative task assignment strategy.Simulation experiments showed that when the task scale was large, the method had a gain of 12%~20% compared with the traditional algorithm in the diff erent scenarios mentioned. |
| format | Article |
| id | doaj-art-3bcf22fba94a4bea968ba7988ac683c2 |
| institution | Kabale University |
| issn | 2096-8930 |
| language | zho |
| publishDate | 2023-03-01 |
| publisher | Post&Telecom Press Co.,LTD |
| record_format | Article |
| series | 天地一体化信息网络 |
| spelling | doaj-art-3bcf22fba94a4bea968ba7988ac683c22025-01-15T02:48:18ZzhoPost&Telecom Press Co.,LTD天地一体化信息网络2096-89302023-03-01421159531876Multi-Ground Station Collaborative Measurement and Control Technology for Giant Constellation SystemYang LIUDi ZHOUMin SHENGJiandong LIShiguang HAOXiaotian ZHENGMeasurement and control technology is the key technology to ensure the effi cient operation, maintenance and management of the constellation system.In recent years, with the continuous expansion of the constellation scale, mega-constellation system has gradually formed, which makes the demand for constellation measurement and control show an explosive growth, which puts forward new requirements for the completion of the constellation system measurement and control tasks.Firstly, the constraints of the megaconstellation system measurement and control tasks and the equipment constraints of the ground measurement and control station were analyzed, and the problem modeling was given; Secondly, an interaction method of the ground station agent based on the learning planning segment was proposed, by introduced the constraint penalty operator and the multi-ground station joint the penalty operator was designed to optimized the objective function.Finally, a multi-ground station Agent reinforcement learning algorithm was proposed to solved the multi-ground station cooperative task assignment strategy.Simulation experiments showed that when the task scale was large, the method had a gain of 12%~20% compared with the traditional algorithm in the diff erent scenarios mentioned.http://www.j-sigin.com.cn/zh/article/doi/10.11959/j.issn.2096-8930.2023001/mega constellationmeasurement and control task planningmulti-ground station coordinationmulti-Agent reinforcement learning |
| spellingShingle | Yang LIU Di ZHOU Min SHENG Jiandong LI Shiguang HAO Xiaotian ZHENG Multi-Ground Station Collaborative Measurement and Control Technology for Giant Constellation System 天地一体化信息网络 mega constellation measurement and control task planning multi-ground station coordination multi-Agent reinforcement learning |
| title | Multi-Ground Station Collaborative Measurement and Control Technology for Giant Constellation System |
| title_full | Multi-Ground Station Collaborative Measurement and Control Technology for Giant Constellation System |
| title_fullStr | Multi-Ground Station Collaborative Measurement and Control Technology for Giant Constellation System |
| title_full_unstemmed | Multi-Ground Station Collaborative Measurement and Control Technology for Giant Constellation System |
| title_short | Multi-Ground Station Collaborative Measurement and Control Technology for Giant Constellation System |
| title_sort | multi ground station collaborative measurement and control technology for giant constellation system |
| topic | mega constellation measurement and control task planning multi-ground station coordination multi-Agent reinforcement learning |
| url | http://www.j-sigin.com.cn/zh/article/doi/10.11959/j.issn.2096-8930.2023001/ |
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