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Flight patterns for clouds exploration with a fleet of UAVs

机译:无人机群进行云探测的飞行模式

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Modeling the cloud microphysics processes is essential to improve our understanding in climate changes and reduce the uncertainties in weather predictions. Aircrafts, remote sensing and ground-based infrastructures provide either sparse or coarse spatial measurements that are not sufficient to develop fine cloud models. UAVs have shown their ability to collect relevant cloud in-situ measures, and can be even more efficient when deployed in fleets. However, collecting relevant cloud data call for specific trajectories: this paper introduces a series of flight patterns dedicated to cloud exploration by a fleet of UAVs. The patterns definition comprise both a priori geometric information and real-time reactions to collected data. Results in simulated clouds assess their relevance for cloud in situ data collection.
机译:云层微微物理过程建模对于改善气候变化中的理解至关重要,并降低天气预报的不确定性。飞机,遥感和基础基础设施提供稀疏或粗糙的空间测量,不足以开发精细云模型。无人机已经表明他们能够收集相关的云原位措施,并且在舰队中部署时可能更有效。但是,收集特定轨迹的相关云数据呼叫:本文介绍了一系列致力于通过UAV的船队浏览的一系列飞行模式。模式定义包括先验几何信息和对收集数据的实时反应。结果在模拟云评估其对云中的相关性。

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