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IMPROVED CAL/VAL OF GOCE GRAVITY GRADIENTS USING TERRESTRIAL DATA

机译：使用地面数据改进了Goce重力梯度的Cal / val

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One method for validating the calibration of the GOCE gravity gradients (GG) utilizes high quality gravity data measured on ground to predict GG in the GOCE data positions in order to compare the results between the GOCE GG and the predicted GG. The calibration is performed in four regions distributed globally by estimating a scale factor between the data sets for each track crossing a calibration area. Each track contains approx. 150 points and each day 1-3 tracks pass a calibration area. The GOCE GGs are affected by a 1/f characteristic noise and has the highest signal to noise ratio in the measurement band (MB) 5-100 mHz. Frequencies outside this band are removed. The GG prediction is performed with leastsquares collocation (LSC) and the resulting GG are merged into a time series of GG model data (EIGEN-5C) by substituting the data over the calibration areas with the predicted data before undergoing a similar filtering as the GG data to extract the data in the MB. Having two comparable data sets requires significant pre-processing of the GOCE data and manual data quality check of the terrestrial data. During the GOCE mission we have reevaluated our calibration data by adding more ground data and adjusted the LSC covariance functions for the data in the calibration areas. The results from both the initial calibration procedure and using the revised terrestrial data selection are presented.
机译：用于验证Goce重力梯度（GG）校准的一种方法利用地面测量的高质量重力数据来预测衰减数据位置中的GG，以比较Goce GG和预测的GG之间的结果。通过估计交叉校准区域的每个轨道之间的数据集之间的刻度因子，在全球分布的四个区域中执行校准。每个轨道都包含约。 150点和每天1-3轨道通过校准区域。 GoCE GGS受到1 / f特征噪声的影响，并且测量频带（MB）5-100MHz中的信噪比最高。删除此频段外部的频率。使用至少在校准区域以预测的数据替换为GG之前将数据与预测数据替换为校准区域，使用最少的校配（LSC）来执行GG预测。在校准区域上通过预测数据将数据与预测数据以类似的滤波器代替校准区域，将结果GG合并为GG模型数据（EIGEN-5C）的时间序列。要在MB中提取数据的数据。拥有两个可比较的数据集需要大量预先处理地面数据的衰减数据和手动数据质量检查。在Goce Mission期间，我们通过添加更多地面数据并调整校准区域中数据的LSC协方差函数来重新评估我们的校准数据。介绍了初始校准程序和使用修订后的地面数据选择的结果。

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