计算机与现代化 ›› 2021, Vol. 0 ›› Issue (02): 104-108.

• 算法设计与分析 • 上一篇    下一篇

基于蚁群算法的导航卫星功率增强任务规划

  

  1. (中国电子科技集团公司第十五研究所系统五部,北京100083)
  • 出版日期:2021-03-01 发布日期:2021-03-01
  • 作者简介:曲建波(1995—),男,四川成都人,硕士研究生,研究方向:卫星应用,E-mail: 15210825203@163.com; 孙剑伟(1974—),男,高级工程师, 硕士,研究方向:卫星运控,卫星应用,E-mail: sunjw@163.com。

Ant Colony Algorithm-based Navigation Satellite Power Enhancement Mission Planning

  1. (Department Five of System, 15th Institute of China Electronics Technology Group Corporation, Beijing 100083, China)
  • Online:2021-03-01 Published:2021-03-01

摘要: 为保障战时区域的导航信号稳定,需要卫星对地面区域进行功率增强,对大规模功率增强任务进行规划能够保障增强效果。本文针对导航卫星功率增强任务规划问题,分析星地可见性以及相邻任务的时间窗口冲突等问题,构建功率增强任务规划模型,选用基于蚁群系统和最大最小蚂蚁系统的自适应蚁群算法,并引入任务收益参数来改进设计算法的寻优策略,在加快算法收敛速度的同时避免陷入局部最优解。实验结果表明,本文的改进蚁群算法对大规模功率增强任务具有很好的规划效果。

关键词: 导航卫星, 任务规划, 功率增强, 蚁群算法

Abstract: In order to ensure the stability of the navigation signal in wartime area, satellites are required to enhance the power of ground area. Planning for large-scale power enhancement missions can ensure the enhancement effect. In this paper, for the problem of navigation satellite power enhancement task planning, the problems of star-ground visibility and time window conflict of adjacent tasks are analyzed. A power enhancement task planning model is constructed, and an adaptive ant colony algorthim based on ant colony system and maximum and minimum ant system is selected. The task revenue parameters are introduced to improve the optimization strategy of the algorithm, and to speed up the convergence rate of the algorithm as well as to avoid falling into the local optimal solution. Experimental results show that the improved ant colony algorithm designed in this paper has a good planning effect for large-scale power enhancement tasks.

Key words: navigation satellite, mission planning, power enhancement, ant colony algorithm