面向星地协同观测规划问题的改进人工蜂群算法

卫星和地面观测资源利用各自搭载的载荷可以完成灾害预报、环境监测、目标发现等任务,地面观测资源可以与卫星配合共同完成观测任务,提升任务观测效果.通过规划将众多的观测任务分配给有限的卫星、地面观测资源来执行可以让协同观测发挥作用,同时得出卫星和地面观测资源的协同任务执行方案,对任务规划提出了很高的要求.基于此,对星地协同观...

Improved artificial bee colony algorithm for satellite-ground cooperative observation planning problem

Satellites and ground observation resources can use their respective loads to complete tasks such as disaster forecasting, environmental monitoring and target discovery. Ground observation resources can cooperate with satellites to complete observation tasks and improve task observation effects. The planning algorithm allocates numerous observation tasks to limited satellites and ground observation resources for execution, which can improve the observation effect. It is a challenge to obtain a mission execution plan for satellite and ground observation resources at the same time. This paper studies the satellite-ground coordinated observation planning problem(SGCOPP), constructs a mathematical model of mission planning, and proposes an improved artificial bee colony(IABC) algorithm and a satellite-ground resource coordinated time selection algorithm(SGRCTSA) based on the characteristics of the problem. This algorithm improves the process of initial population generation, colony optimization process and individual elimination process to enhance its search optimization ability. A large number of experiments verify the effectiveness of the proposed IABC algorithm to solve the SGCOPP. Results show that the IABC algorithm performs better than state-of-the-art algorithms, which can provide technical support for cross-domain collaborative observation research.