论文标题
用于交流图像敏捷地球观察卫星的多strip观察计划问题
Multi-strip observation scheduling problem for ac-tive-imaging agile earth observation satellites
论文作者
论文摘要
活跃成像的敏捷地球观测卫星（AI-Aea）是新一代敏捷的地球观测卫星（AEOS）。随着观察和主动Im-Ever的更新功能，AI-Aeos的观察能力提高了AEOS的能力，并提供了观察地面目标的其他方法。然而，这使得这些敏捷地球观察卫星的观察计划问题更加复杂，尤其是在考虑多发性地面目标时。在本文中，我们研究了主动图像敏捷地球观察卫星（MOSP）的多strip观察计划问题。为MOSP提供了双目标优化模型，以及一种自适应的双目标模因算法，该算法整合了自适应大型邻里搜索算法（ALNS）和非主导分类遗传算法II（NSGA-II）的组合功率。提出了广泛的计算实验的结果，这些结果揭示了ALNS和NSGA-II在一致的工作中产生了出色的结果。我们的模型比现有模型更通用，并在应用问题解决方面提供了增强的功能。
Active-imaging agile earth observation satellite (AI-AEOS) is a new generation agile earth observation satellite (AEOS). With renewed capabilities in observation and active im-aging, AI-AEOS improves upon the observation capabilities of AEOS and provide additional ways to observe ground targets. This however makes the observation scheduling problem for these agile earth observation satellite more complex, especially when considering multi-strip ground targets. In this paper, we investigate the multi-strip observation scheduling problem for an active-image agile earth observation satellite (MOSP). A bi-objective optimization model is presented for MOSP along with an adaptive bi-objective memetic algorithm which integrates the combined power of an adaptive large neighborhood search algorithm (ALNS) and a nondominated sorting genetic algorithm II (NSGA-II). Results of extensive computa-tional experiments are presented which disclose that ALNS and NSGA-II when worked in unison produced superior outcomes. Our model is more versatile than existing models and provide enhanced capabilities in applied problem solving.
