Most earth observation satellites(EOSs)are low-orbit satellites equipped with optical sensors that cannot see through clouds.Hence,cloud coverage,high dynamics,and cloud uncertainties are important issues in the sched...Most earth observation satellites(EOSs)are low-orbit satellites equipped with optical sensors that cannot see through clouds.Hence,cloud coverage,high dynamics,and cloud uncertainties are important issues in the scheduling of EOSs.The proactive-reactive scheduling framework has been proven to be effective and efficient for the uncertain scheduling problem and has been extensively employed.Numerous studies have been conducted on methods for the proactive scheduling of EOSs,including expectation,chance-constrained,and robust optimization models and the relevant solution algorithms.This study focuses on the reactive scheduling of EOSs under cloud uncertainties.First,using an example,we describe the reactive scheduling problem in detail,clarifying its significance and key issues.Considering the two key objectives of observation profits and scheduling stability,we construct a multi-objective optimization mathematical model.Then,we obtain the possible disruptions of EOS scheduling during execution under cloud uncertainties,adopting an event-driven policy for the reactive scheduling.For the different disruptions,different reactive scheduling algorithms are designed.Finally,numerous simulation experiments are conducted to verify the feasibility and effectiveness of the proposed reactive scheduling algorithms.The experimental results show that the reactive scheduling algorithms can both improve observation profits and reduce system perturbations.展开更多
上升气流是成云致雨的基本条件之一。本文利用河北省2017年5月一次层积混合云的机载云物理探测系统测量资料,研究了云中上升气流速度分布,云微结构特征以及二者的相关性。结果表明:云中上升气流速度随高度呈抛物线型分布,云底部较小(0.7...上升气流是成云致雨的基本条件之一。本文利用河北省2017年5月一次层积混合云的机载云物理探测系统测量资料,研究了云中上升气流速度分布,云微结构特征以及二者的相关性。结果表明:云中上升气流速度随高度呈抛物线型分布,云底部较小(0.75±0.52 m s^(−1)),云中部最大(3.64±2 m s^(−1)),云顶部最小(0.32±0.29 m s^(−1));发现随高度增加,云中上升气流区内冰粒子形状依次以片状、针状、柱状为主;暖云上升气流区中,上升气流速度与液态含水量正相关,相关系数为0.61;强垂直气流条件下云滴数浓度、最大云滴尺度大于弱垂直气流相应的数值,强垂直气流云粒子谱更符合Г函数分布。展开更多
基金supported by the National Natural Science Foundation of China(7180121871701067+3 种基金72071075)the Research Project of National University of Defense Technology(ZK18-03-16)the Natural Science Foundation of Hunan Province,China(2020JJ46722019JJ50039)。
文摘Most earth observation satellites(EOSs)are low-orbit satellites equipped with optical sensors that cannot see through clouds.Hence,cloud coverage,high dynamics,and cloud uncertainties are important issues in the scheduling of EOSs.The proactive-reactive scheduling framework has been proven to be effective and efficient for the uncertain scheduling problem and has been extensively employed.Numerous studies have been conducted on methods for the proactive scheduling of EOSs,including expectation,chance-constrained,and robust optimization models and the relevant solution algorithms.This study focuses on the reactive scheduling of EOSs under cloud uncertainties.First,using an example,we describe the reactive scheduling problem in detail,clarifying its significance and key issues.Considering the two key objectives of observation profits and scheduling stability,we construct a multi-objective optimization mathematical model.Then,we obtain the possible disruptions of EOS scheduling during execution under cloud uncertainties,adopting an event-driven policy for the reactive scheduling.For the different disruptions,different reactive scheduling algorithms are designed.Finally,numerous simulation experiments are conducted to verify the feasibility and effectiveness of the proposed reactive scheduling algorithms.The experimental results show that the reactive scheduling algorithms can both improve observation profits and reduce system perturbations.
文摘上升气流是成云致雨的基本条件之一。本文利用河北省2017年5月一次层积混合云的机载云物理探测系统测量资料,研究了云中上升气流速度分布,云微结构特征以及二者的相关性。结果表明:云中上升气流速度随高度呈抛物线型分布,云底部较小(0.75±0.52 m s^(−1)),云中部最大(3.64±2 m s^(−1)),云顶部最小(0.32±0.29 m s^(−1));发现随高度增加,云中上升气流区内冰粒子形状依次以片状、针状、柱状为主;暖云上升气流区中,上升气流速度与液态含水量正相关,相关系数为0.61;强垂直气流条件下云滴数浓度、最大云滴尺度大于弱垂直气流相应的数值,强垂直气流云粒子谱更符合Г函数分布。
