基于混合免疫遗传算法的多类型成像卫星任务规划  

Mission Planning of Multi-type Imaging Satellites Based on Hybrid Immune Genetic Algorithm

作　　者：杨阳 刘德生 常青 Yang Yang;Liu Desheng;Chang Qing(Complex Electronic System Simulation Laboratory,Space Engineering University,Beijing 101400,China)

机构地区：[1]航天工程大学复杂电子系统仿真实验室,北京101400

出　　处：《兵工自动化》2025年第3期13-19,共7页Ordnance Industry Automation

基　　金：国防科技重点实验室基金(614201001032202)。

摘　　要：针对如何在卫星应用领域有效进行任务规划的问题,构建多类型成像卫星任务规划模型,并提出一种混合免疫遗传算法(hybrid immune genetic algorithm,HIGA)对模型进行求解。设计符合多类型成像卫星任务规划特点的编解码策略,引入自适应机制,禁忌搜索思想,定义基于抗体浓度和适应度的选择策略以及新的疫苗接种操作。通过仿真算例分析,结果表明:所提算法可解决多类型卫星任务规划问题,有效改善免疫遗传算法易早熟收敛和陷入局部最优等问题;与对比算法相比,该算法可取得更快的收敛速度和更优的规划结果,且进行大规模的任务规划时仍可取得较优的规划结果。Aiming at the problem of mission planning in the field of satellite application,a mission planning model for multi-type imaging satellites is constructed,and a hybrid immune genetic algorithm(HIGA)is proposed to solve the model.An encoding and decoding strategy is designed according to the characteristics of multi-type imaging satellite task planning,an adaptive mechanism and a tabu search idea are introduced,and a selection strategy based on antibody concentration and fitness and a new vaccination operation are defined.The simulation results show that the proposed algorithm can solve the problem of multi-type satellite mission planning,and effectively improve the problems of immune genetic algorithm,such as premature convergence and falling into local optimum.Compared with the comparative algorithm,the proposed algorithm can achieve faster convergence speed and better planning results,and can also achieve better planning results when planning large-scale missions.

关 键 词：多类型成像卫星 任务规划 免疫遗传 智能优化算法 

分 类 号：P171.3[天文地球—天文学]