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Optimal mission scheduling for hybrid synthetic aperture radar satellite constellation based on weighting factors
Aerospace Science and Technology ( IF 5.0 ) Pub Date : 2020-10-20 , DOI: 10.1016/j.ast.2020.106287
Hongrae Kim , Young-Keun Chang

Hybrid synthetic aperture radar (SAR) satellites, unlike active SAR satellites using phased array antennas, mainly acquire images using mechanical beam steering and, to some extent, through electronic beam steering. Therefore, the image acquisition capability of a hybrid SAR satellite is affected by its agility. An optimal mission plan considering the image downlink and command uplink related to mission operation and maneuvering characteristics for image acquisition is required to maximize the capability of such a satellite. In this study, we developed a model of the timeline elements needed for image acquisition using a SAR satellite and a mission plan considering multiple passes of SAR constellation satellites. The proposed mission plan involves optimization using dynamic programming and a genetic algorithm. Dynamic programming is applied to enable the satellite to image the area of interest (AoI) as effectively as possible in a single pass. In addition, the mission plan was optimized by adjusting the weighting factor of each target using the genetic algorithm to enable targets in the AoI to be imaged quickly in multiple passes. The mission plan was implemented according to the proposed technique, and it was confirmed that the method of assigning the weighting factors of the targets could affect the number of passes required to image all the targets in the AoI. The mission performance was also improved compared to that of the conventional method in terms of minimizing the number of mission passes and considering a mission plan with multiple passes.



中文翻译:

基于加权因子的混合孔径雷达卫星星座最优任务调度

混合式合成孔径雷达(SAR)卫星与使用相控阵天线的有源SAR卫星不同,它主要使用机械波束控制,并在某种程度上通过电子波束控制来获取图像。因此,混合SAR卫星的图像采集能力受其敏捷性影响。为了使这种卫星的能力最大化,需要考虑与任务运行和图像特征相关的操纵特性有关的图像下行链路和命令上行链路的最佳任务计划。在这项研究中,我们开发了使用SAR卫星进行图像采集所需的时间轴元素模型,以及考虑了SAR星座卫星多次通过的任务计划。拟议的任务计划涉及使用动态规划和遗传算法进行优化。应用动态编程使卫星能够在单次通过中尽可能有效地成像目标区域(AoI)。此外,通过使用遗传算法调整每个目标的权重因子来优化任务计划,以使AoI中的目标能够在多次扫描中快速成像。任务计划是根据所提出的技术实施的,已确认分配目标加权因子的方法可能会影响对AoI中所有目标成像所需的通过次数。与传统方法相比,在减少任务通过次数和考虑多次通过的任务计划方面,任务性能也得到了改善。此外,通过使用遗传算法调整每个目标的权重因子来优化任务计划,以使AoI中的目标能够在多次扫描中快速成像。任务计划是根据所提出的技术实施的,已确认分配目标加权因子的方法可能会影响对AoI中所有目标成像所需的通过次数。与传统方法相比,在减少任务通过次数和考虑多次通过的任务计划方面,任务性能也得到了改善。此外,通过使用遗传算法调整每个目标的权重因子来优化任务计划,以使AoI中的目标能够在多次扫描中快速成像。任务计划是根据所提出的技术实施的,已确认分配目标加权因子的方法可能会影响对AoI中所有目标成像所需的通过次数。与传统方法相比,在减少任务通过次数和考虑多次通过的任务计划方面,任务性能也得到了改善。任务计划是根据所提出的技术实施的,已确认分配目标加权因子的方法可能会影响对AoI中所有目标成像所需的通过次数。与传统方法相比,在减少任务通过次数和考虑多次通过的任务计划方面,任务性能也得到了改善。任务计划是根据所提出的技术实施的,已确认分配目标加权因子的方法可能会影响对AoI中所有目标成像所需的通过次数。与传统方法相比,在减少任务通过次数和考虑多次通过的任务计划方面,任务性能也得到了改善。

更新日期:2020-10-30
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