敏捷成像卫星多星密集任务调度方法

 面向应急观测需求,对敏捷成像卫星多星密集点目标观测任务调度问题进行研究。针对敏捷成像卫星观测特点,综合考虑卫星可观测时间窗口、任务间卫星姿态调整时间、卫星最长连续工作时间、星上存储容量、卫星能量等约束,建立多星任务调度模型。提出了一种改进的蚁群优化(ACO)算法对调度模型进行求解。该算法借鉴了蚁群系统(ACS)和最大最小蚂蚁系统(MMAS)的思想,结合调度相关约束设计寻优策略和信息素更新策略。引入任务优先级、最早及最晚可观测时间等因素来控制转移概率。仿真结果验证了模型和算法的有效性。

Intensive Task Scheduling Method for Multi-agile Imaging Satellites

Considering the observing request in an emergency, intentive observing task scheduling of multi-agile imaging satellites is studied. A scheduling model is established which considers such complex constraints as the visible time window, the attitude changing duration between tasks, the maximal successive working duration, energy and storage capacity restriction, etc. An improved ant colony optimization (ACO) algorithm is designed to solve the problem, which is based on ant colony system (ACS) and max-min ant system (MMAS). The searching strategy and pheromone update strategy are designed according to the scheduling constraints. The factors of task priority and bounds of the visible time are introduced into transfer rules to control the transition probability. Simulation results show the effectiveness and efficiency of our approach.