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.

中文翻译：

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云不确定性下的多个EOS的反应式调度：模型和算法

大多数地球观测卫星（EOS）是配备了无法穿透云层的光学传感器的低轨道卫星。因此，云覆盖，高动态性和云不确定性是EOS调度中的重要问题。主动-被动调度框架已被证明对于不确定的调度问题是有效和高效的，并已被广泛采用。关于主动调度EOS的方法，已经进行了许多研究，包括期望，机会受限和鲁棒的优化模型以及相关的求解算法。这项研究的重点是在云不确定性下的EOS的反应式调度。首先，通过一个例子，我们详细描述了无功调度问题，阐明了其重要性和关键问题。考虑到观测收益和调度稳定性这两个关键目标，我们构建了一个多目标优化数学模型。然后，我们获得了在云不确定性下执行期间EOS调度的可能中断，采用事件驱动策略进行反应式调度。对于不同的中断，设计了不同的反应式调度算法。最后，进行了大量的仿真实验，以验证所提出的反应式调度算法的可行性和有效性。实验结果表明，反应式调度算法既可以提高观测收益，又可以减少系统扰动。我们在云不确定性下执行期间获得了EOS调度的可能中断，采用事件驱动策略进行反应式调度。对于不同的中断，设计了不同的反应式调度算法。最后，进行了大量的仿真实验，以验证所提出的反应式调度算法的可行性和有效性。实验结果表明，反应式调度算法既可以提高观测收益，又可以减少系统扰动。我们在云不确定性下执行期间获得了EOS调度的可能中断，采用事件驱动策略进行反应式调度。对于不同的中断，设计了不同的反应式调度算法。最后，进行了大量的仿真实验，以验证所提出的反应式调度算法的可行性和有效性。实验结果表明，反应式调度算法既可以提高观测收益，又可以减少系统扰动。