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An anytime branch and bound algorithm for agile earth observation satellite onboard scheduling

机译:敏捷地球观测卫星机载调度的随时分支定界算法

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摘要

To fulfill the mission of targets recognition over sea, a bi-satellite cluster composed of an autonomous low resolution satellite (LRS) leading the formation for targets detection and a trailing agile high resolution satellite (HRS) for targets recognition is considered. This paper focuses on the development of a method that is able to generate a schedule plan onboard the HRS taking into account the information received from the LRS, which amounts to solving an agile earth observation satellite (AEOS) scheduling problem. The main contributions of this paper are two folds: a mathematical model for formulating the AEOS scheduling problem, and an anytime branch and bound algorithm for problem solution. Experimental results on a set of representative scenarios show that the proposed algorithm is effective which promotes significantly the bi-satellite cluster to improve the efficiency of targets recognition over sea as opposed to traditional methods where a large number of satellites are required to work coordinately. In particular, in a scenario over a 500 km × 2000 km sea area involving 25 targets, the performance of the bi-satellite cluster amounts to the coordination of 30 high resolution satellites.
机译:为了完成海上目标识别的任务,考虑了由自主低分辨率卫星(LRS)和目标敏捷的尾随敏捷高分辨率卫星(HRS)组成的双卫星集群,该卫星领导着目标检测的形成。本文关注于一种方法的开发,该方法能够考虑到从LRS接收到的信息而在HRS上生成调度计划,这相当于解决了敏捷地球观测卫星(AEOS)的调度问题。本文的主要贡献有两个方面:建立AEOS调度问题的数学模型和解决问题的随时分支定界算法。在一组代表性场景上的实验结果表明,与需要大量卫星协同工作的传统方法相比,该算法有效地促进了双卫星集群的发展,从而提高了海上目标识别的效率。特别是,在500 km×2000 km海域中涉及25个目标的情况下,双卫星集群的性能相当于30颗高分辨率卫星的协调。

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