Design of agile satellite constellation based on hybrid-resampling particle swarm optimization method

被引:29
|
作者
Wang, Xiaohui [1 ]
Zhang, Hao [1 ]
Bai, Shengzhou [1 ]
Yue, Yuxian [1 ]
机构
[1] Beihang Univ, Sch Astronaut, Beijing 102206, Peoples R China
基金
中国国家自然科学基金;
关键词
Constellation design; Agile satellite; Particle swarm optimization; Hybrid resampling; GEOMETRIC ANALYSIS; COVERAGE; COMMUNICATION; NETWORK; NAVIGATION; ORBIT;
D O I
10.1016/j.actaastro.2020.09.040
中图分类号
V [航空、航天];
学科分类号
08 ; 0825 ;
摘要
In recent years, on-orbit constellations providing global communication and observation services have attracted widespread attention for economic and military interests. Thus, the design of satellite constellations has become a popular topic, which is mainly approached using different optimization methods. However, there are still some drawbacks to traditional methods, such as poor convergence and long computation time, which usually limit engineering applications. In this paper, a novel optimization method, the hybrid-resampling particle swarm optimization (HRPSO) algorithm, is proposed that provide higher efficiency for constellation design. The simulation results showed that the HRPSO algorithm is more efficient than the standard particle swarm optimization (PSO) algorithm and other improved resampling particle swarm optimization (RPSO) algorithms. Therefore, the HRPSO algorithm is expected to be a practical choice for constellation design.
引用
收藏
页码:595 / 605
页数:11
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