基于改进遗传算法对小卫星星群任务规划研究

Mission Planning for Small Satellite Constellations Based on Improved Genetic Algorithm

针对小卫星星群任务运行特点,建立小卫星星群多任务规划问题模型,提出了基于成像任务时间及任务均衡度的多指标优化函数.针对所建模型,采用改进型遗传算法,引入资源随机分配的解码策略及精英保留策略,保证了算法的全局收敛性,提高了算法的性能.通过仿真算例,验证了算法在解决小卫星星群多目标任务规划问题上的有效性.

Based on operational features of small satellite constellation, a multi-task mission planning problem model for small satellite constellation is established, and a multi-index optimization function based on imaging task period and equilibration is proposed. Furthermore, an improved genetic algorithm involving strategies of random allocation of resources as well as elite population reservation is applied to the established model. The algorithm improves the efficiency of related solution and guarantees the convergence of the final result. The simulation result shows that the improved genetic algorithm is applicable and effective to the specific needs of mission planning problem for small satellite constellation.