在气象领域中，气象目标在整个探测范围内具有数目多、区域散、面积小、形状不规则等特征，使用常规插值算法重构的三维云层图易造成图像信息准确性不高，离散或体积较小的目标信息丢失等问题，使得重建的三维图像常常不能满足实时业务的需求。本文根据雷达实际观测数据，提出并实现了一种立方体网格插值算法，将不规则的雷达锥面数据映射到规则的三维数据场中，并结合Marching Cubes算法对气象雷达数据进行三维重建实验。实验结果表明，使用本文提出的算法得到的三维重建云层图能较为准确地反映出气象目标的基本特征及其空间分布，满足气象业务需要，为气象目标实时跟踪和准确预报提供了参考依据。
In the meteorological field, meteorological objects have many targets, scattered regions, small areas, and irregular shapes in the whole detection range. Using conventional interpolation algorithms to reconstruct three-dimensional cloud image may result in low accuracy of image information and discrete and small object image information loss which makes the reconstructed three-dimensional cloud image data often not to meet the needs of real-time business. Based on the actual observation data of radar, this paper proposes and implements a cubic grid interpolation algorithm, which maps the irregular radar cone data into the regular 3D data field, and combines the Marching Cubes algorithm to perform 3D reconstruction experiments on meteorological radar data. The experimental results show that the 3D reconstruction cloud map obtained by the proposed algorithm can accurately reflect the basic characteristics and spatial distribution of meteorological targets, which meet the meteorological service requirements, and provide a reference for real-time tracking and accurate prediction of meteorological targets.
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