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A new strategy for processing airborne gravity data

机译:处理机载重力数据的新策略

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摘要

We present a new approach for regional gravity field analysis from airborne gravity data, which combines separate processing steps into one inversion scheme. The approach uses a spectral representation of the Earth's gravity field in terms of a series of harmonic base functions, expressed in a local Cartesian reference frame. The parameters of this representation are estimated using least-squares techniques. Special emphasis is put on the proper modeling of data noise. Frequency-dependent data weighting is applied to handle colored noise, which replaces the traditional method of low-pass filtering and crossover adjustment. To suppress model errors at the highest spatial frequencies, first-order Tikhonov reg-ularization is applied. The performance of the developed technique is assessed for the inversion of gravity disturbances into the disturbing potential, using simulated data.
机译:我们提出了一种从机载重力数据进行区域重力场分析的新方法,该方法将单独的处理步骤组合为一个反演方案。该方法以一系列笛卡尔基函数的形式使用地球重力场的频谱表示形式,以局部笛卡尔坐标系表示。使用最小二乘法估计该表示的参数。特别强调数据噪声的正确建模。频率相关的数据加权应用于处理彩色噪声,它取代了传统的低通滤波和分频调整方法。为了抑制最高空间频率处的模型误差,应用了一阶Tikhonov正则化。使用模拟数据评估了将重力扰动转化为扰动电位的先进技术的性能。

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