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贪婪搜索算法在卫星调度中的应用研究

单国厚1,刘建2,水艳2,李丽华2,喻光晔2   

  1. 1. 中国科学技术大学
    2. 淮河流域水资源保护局 淮河水资源保护科学研究所
  • 收稿日期:2016-11-16 修回日期:2017-01-04 发布日期:2017-01-04
  • 通讯作者: 单国厚

Research on Application of Greedy Search Algorithm into Satellite Schedule

  • Received:2016-11-16 Revised:2017-01-04 Online:2017-01-04
  • Contact: Guo-Hou SHAN

摘要: 针对采用天气预报的滞后云层进行卫星调度影响观测图像质量和观测收益的问题,提出一种获取实时云层的数学模型,并基于此构建考虑实时变换云层的敏捷观测卫星调度模型。由于贪婪搜索算法具有局部优化的特性,能够充分考虑卫星观测的云层和有限存储资源等约束,因而研究了贪婪搜索算法在该卫星调度问题中的应用。首先,贪婪搜索算法优先考虑观测任务的云层遮挡,并根据云层遮挡大小,计算待观测任务的图像质量,将之排序选择待观测的任务;其次,结合任务的大小、截止时间和卫星的存储资源约束,选择能够给观测收益带来最大化的任务;最后,进行观测和任务传送。仿真实验表明,在任务数为100的情况下,采用贪婪搜索算法进行卫星调度的任务收益比常用于卫星调度的动态规划算法和局部搜索算法分别提高14.82%和10.32%;并且同等条件下,采用贪婪搜索算法得到的观测图像的质量比其他两种方法得到的图像质量更高。实验结果表明,贪婪搜索算法在实际卫星调度中,能够有效地提高图像观测质量和任务观测收益。

关键词: 关键词: 卫星调度, 贪婪搜索算法, 近似实时云层, 任务收益, 图像质量

Abstract: In order to solve the problem that observational image quality and profits are low in satellite schedule adopted lagged weather forecast cloud information, a mathematic model capturing real-time cloud distribution is proposed. The agile satellite schedule model is also built based on the real-time cloud information. Considering the local optimization of greedy search algorithm (GSA), it was applied to solve this schedule problem. Firstly, GSA had a preference of tasks with high observational image quality calculated by considering tasks’ cloud coverage and ranked the task lists based on the preference; Secondly, it selected tasks to maximize profits according to task size, deadline and satellite storage; Finally, satellite observed the tasks and transmitted them according to their ability of improving profits. Simulation experiments show that the satellite adopting GSA could improve observational profits by 14.82% and 10.32% than taking the dynamic programming algorithm (DPA) and local search algorithm (LSA) respectively. Besides, the image quality of applying GSA is higher than taking DPA and LSA in the same circumstance. The experimental results show that GSA can effectively improve the image quality and observational profits of satellite schedule.

Key words: Keywords: satellite schedule, greedy search algorithm optimization, nearly real-time cloud, task profits, image quality

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