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在重磁等离散数据处理中,通常需要首先按预设网格对离散数据进行网格化,继而进行后续处理.当野外测量途径沼泽、水域、凹陷等不能直接获取测量数据时,网格化后的数据在该区域通常表现为数据空缺,常规处理如此尚可,但若资料进行场源反演等特殊计算时,需要将空缺补全,本文则针对此问题进行研究.本文介绍了一种基于2D傅立叶变换的凸集投影迭代算法,能够直接对网格数据进行计算,无需坐标信息,直接补全缺失数据.该方法具有计算直接、简单、精算精度高的优点.实际数据对比分析表明,在足够的计算迭代后,计算结果数值精度与最小曲率方法相当.
In the case of gravity and magnetic discrete data processing, it is usually necessary to first mesh the discrete data according to a preset grid and then perform subsequent processing. When the measurement data of the field measurement channels such as swamps, waters and depressions can not be obtained directly, the gridding The data usually appear as data vacancy in the region, so the conventional processing is still acceptable, but if the data are subject to special calculation such as field inversion, the vacancy should be complemented, and the paper studies the problem.This paper introduces a The convex projection projection iterative algorithm based on 2D Fourier transform can directly calculate the grid data without coordinate information and directly fill in the missing data.This method has the advantages of direct calculation, simple calculation and high accuracy.The comparison of actual data shows that, After enough computational iterations, the numerical accuracy of the calculated results is comparable to the method of minimum curvature.