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Semi-vectorization: an efficient technique for synthesis and analysis of gravity gradiometry data

机译:半向量化:一种合成和分析重力梯度数据的有效技术

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摘要

The harmonic synthesis and analysis of the elements of gravitational tensor can be done in few minutes if a suitable programming algorithm is used. Vectorization is an efficient technique for such processes, but the size of matrices will increase when the resolution of synthesis or analysis is high; say higher than 0.5° × 0.5°. Here, we present a technique to manage the computer memory and computational time by excluding one computational loop from the matrix products and we call this method semi-vectorization. Based on this technique, we synthesize the gravitational tensor using the EGM96 geopotential model and after that we analyze the tensor for recovering the geopotential coefficients. MATLAB codes are provided which are able to analyze 224 millions gradiometric data, corresponding to a global grid of 2.5′ × 2.5′ on a sphere in 1,093 s by a personal computer with 2 Gb RAM.
机译:如果使用合适的编程算法,则可以在几分钟内完成重力张量元素的谐波合成和分析。矢量化是用于此类过程的一种有效技术,但是当合成或分析的分辨率较高时,矩阵的大小将增加;例如高于0.5°×0.5°。在这里,我们提出了一种通过从矩阵乘积中排除一个计算循环来管理计算机内存和计算时间的技术,我们将此方法称为半向量化。基于此技术,我们使用EGM96地势模型合成重力张量,然后分析张量以恢复地势系数。提供了MATLAB代码,该代码能够通过具有2 Gb RAM的个人计算机来分析1.209 s内球体上的2.5'×2.5'全局网格的2.24亿个梯度数据。

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