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Multi satellites scheduling algorithm based on task merging mechanism

机译:基于任务合并机制的多卫星调度算法

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Earth observation satellites are platforms equipped with optical instruments that orbit the earth to take photographs of specific areas at users’ requests. Compared with huge user requests, satellites are still scanty resources. For some task, the satellite has to roll its camera to take the desired image. However,manysatellites are rigidly restricted on maneuverability. As a result, the performances of satellites are greatly confined. Therefore, we need a scientific observation plan to weaken the constraints arising from satellites’ poor slew ability. To solve the problem we present a multi satellites scheduling algorithm based on task merging mechanism. The algorithm partitions the problem into two sub-problems: task assignment and task merging. In task assignment, we propose an adaptive ant colony optimization algorithm to select specific time window for each task, creating a task list for each satellite. In task merging, we propose the concept of task combination and develop a dynamic programming algorithm to find the best merging plan for each satellite. The two sub-problems are logically coupled; a valid observation plan will be got after much iteration. Finally, a series of test examples are given out, which demonstrate our algorithm to be effective.
机译:对地观测卫星是指配备有光学仪器的平台,这些仪器可以绕地球旋转以根据用户的要求拍摄特定区域的照片。与庞大的用户请求相比,卫星仍然是稀缺资源。对于某些任务,卫星必须转动其摄像机才能拍摄所需的图像。但是,许多卫星在操纵性上受到严格限制。结果,极大地限制了卫星的性能。因此,我们需要一个科学的观测计划,以减轻由于卫星回转能力差而产生的限制。为了解决这个问题,我们提出了一种基于任务合并机制的多卫星调度算法。该算法将问题分为两个子问题:任务分配和任务合并。在任务分配中,我们提出了一种自适应蚁群优化算法来为每个任务选择特定的时间窗口,为每个卫星创建一个任务列表。在任务合并中,我们提出了任务合并的概念,并开发了一种动态规划算法来为每颗卫星找到最佳的合并计划。这两个子问题在逻辑上是耦合的。经过多次迭代,才能获得有效的观察计划。最后,给出了一系列测试示例,证明了我们的算法是有效的。

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