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Analysis of 1/f noise characteristics of geo-signals

机译:地理信号1 / F噪声特性分析

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The superposition of 1/f~(gamma) and white noise is a useful noise-model used in many fields. The determination of the spectral exponent gamma and the mixture ratios of these noises are important in many applications such as GPS (Global Positioning System) time series residual noise, soil radon gas emanation (ambient noise) data and the seismic background noise. GPS data is used to estimate the surface displacement and the strain velocity of the earth. Reliable estimations of these quantities require accurate models and proper error analysis. Radon data also provide insight on temporal variation of soil gas in porous and permeable part of the shallow crust of the earth. The anomalies (abrupt amplitude changes) in gas emanation are found to be related to the seismic activities. We analyze GPS residual noise, radon data and background noise data by a wavelet-based method which relies on a line fitting operation to the difference sequence constructed from the variance progression of the wavelet coefficients. The main goal is to estimate the noise characteristics (gamma parameter and the noise amplitudes) reliably. We show that the 1/f~(gamma) noise part in the GPS residual signals is measured as the flicker noise (gamma(approx=)1) (induced by atmospheric effects, mismodeled satellite orbits, etc.). We also present the analysis of soil radon gas emanation data and the seismic background noise, both of which follow the 1/f noise superposed by white noise similar to GPS noise. We discuss the wavelet-based analysis method in detail and present results obtained with real data.
机译:1 / f〜(伽马)和白噪声的叠加是许多领域中使用的有用噪声模型。这些噪声的光谱指数γ和混合比的测定在许多应用中是重要的,例如GPS(全球定位系统)时间序列剩余噪声,土氡气散发(环境噪声)数据和地震背景噪声。 GPS数据用于估计地面的表面位移和应变速度。这些数量的可靠估计需要准确的模型和适当的错误分析。氡数据还提供了对地球浅地壳多孔和可渗透部分中土壤气体的时间变化的洞察。发现气体散发中的异常(突然幅度变化)与地震活动有关。我们通过基于小波的方法分析GPS残差噪声,氡数据和背景噪声数据,该方法依赖于从小波系数的方差进展构成的差分序列的线拟合操作。主要目标是可靠地估计噪声特性(伽马参数和噪声幅度)。我们表明,GPS残差信号中的1 / F〜(Gamma)噪声部分被测量为闪烁噪声(伽马(约=)1)(由大气效应引起,毫不掩模卫星轨道等)。我们还介绍了土壤氡气散发数据和地震背景噪声的分析,两者都遵循与GPS噪声相似的白噪声叠加的1 / F噪声。我们详细讨论了基于小波的分析方法,并通过实际数据获得了现有的结果。

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