针对强电磁干扰极易掩盖微弱的大地电磁有用信号,本文结合奇异值分解在去噪方面的优越性,提出基于自适应多分辨率奇异值分解(Adaptive Multi-Resolution Singular Value Decomposition,AMRSVD)的大地电磁数据处理方法.首先对大地电磁数据构建Hankel矩阵,利用MRSVD得到不同分辨率的近似信号和细节信号;然后选用近似信号和细节信号的标准差差值,对大地电磁数据进行信噪辨识;接着结合MRSVD和相邻细节信号的标准差差值,提出先验信息未知情况下的AMRSVD法;最后对辨识出的强干扰运用AMRSVD去除噪声,重构有用信号.实验结果表明,该方法的处理效率高,能有效分离出相关性较强的噪声,时间序列和视电阻率-相位曲线均得到有效改善.
Commonly, geomagnetic prospection is performed via scalar magnetometers that measure values of the total magnetic intensity. Recent developments of superconducting quantum interference devices have led to their integration in full tensor magnetic gradiometry systems consisting of planar‐type first‐order gradiometers and magnetometers fabricated in thin‐film technology. With these systems measuring directly the magnetic gradient tensor and field vector, a significantly higher magnetic and spatial resolution of the magnetic maps is yield than those produced via conventional magnetometers. In order to preserve the high data quality in this work, we develop a workflow containing all the necessary steps for generating the gradient tensor and field vector quantities from the raw measurement data up to their integration into highresolution, lownoise, and artefactless two‐dimensional maps of the magnetic field vector. The gradient tensor components are processed by superposition of the balanced gradiometer signals and rotation into an Earth‐centred Earth‐fixed coordinate frame. As the magnetometers have sensitivity lower than that of gradiometers and the total magnetic intensity is not directly recorded, we employ Hilbert‐like transforms, e.g., integration of the gradient tensor components or the conversion of the total magnetic intensity derived by calibrated magnetometer readings to obtain these values. This can lead to a better interpretation of the measured magnetic anomalies of the Earth's magnetic field that is possible from scalar total magnetic intensity measurements. Our conclusions are drawn from the application of these algorithms on a survey acquired in South Africa containing full tensor magnetic gradiometry data. 相似文献