Distributed Satellite Cluster Laser Networking Algorithm with Double-Layer Markov DRL Architecture  

作　　者：Yuanzhi He Biao Sheng Hao Yin Yun Liu Yingchao Zhang 

机构地区：[1]School of Systems Science and Engineering,Sun Yat-Sen University,Guangzhou 100876,China [2]Institute of Systems Engineering,AMS,PLA,Beijing 100000,China

出　　处：《Space(Science & Technology)》2023年第1期80-97,共18页空间科学与技术（英文）

摘　　要：Considering the demand of distributed satellite clusters for high-speed information communication in the future,this paper establishes a laser network model based on optical multibeam antenna.At present,there are still some networking and reconstruction problems,such as network connectivity,duration,and stability.To address them,the paper develops a multiobjective optimization model for the laser networking of distributed satellite clusters,which aims to maximize network connectivity and network duration and minimize the perturbation of the network connection matrix.The model is constructed under the constraints of multibeam antenna capability,the visibility of satellites in clusters,and network connectivity.From the perspectives of the optimization effect and timeliness of the optimization algorithm,a deep reinforcement learning algorithm is proposed,which is based on a double-layer Markov decision model,to meet the needs of on-orbit intelligent networking and dynamic reconstruction of distributed satellite clusters.Simulation results show that the algorithm features flexible architecture,excellent networking performance,and strong real-time performance.When the optimization results are similar,the proposed algorithm outperforms the nonsorted genetic algorithm II algorithm and the particle swarm optimization algorithm in terms of solution speed.

关 键 词：stability network optimization 

分 类 号：V474[航空宇航科学与技术—飞行器设计]