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北京 GNSS 地震监测用时间序列生成的试验研究

Experimental Research on GNSS Time Series Generation for Seismic Monitoring in Beijing

Geomatics Observation / 2020,2(4): 127-137 / 2020-09-23 807 988

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• Authors: 吴培稚      胡乐银*      赵桂儒      徐平      邢成起      季红      柴金翼      梁芳      施玉芳     
• Information:

  北京市地震局，北京

• Keywords: GNSS; Noise Modeling; Linear decomposition; Low pass filtering; Earthquake monitoring GNSS；噪声；短期线性分解；低通滤波；地震监测
• Abstract: Beijing GNSS continuous observation network has many factors that are not conducive to earthquake monitoring, such as a small coverage of the network, too many soil sites, low crustal movement level, and high noise level, etc. In this paper, mutation, continuous smoothness, shared noise, and station noise are used to decompose the time series of station locations. Based on the characteristic that continuous smooth changes can be linearly fitted, the short-term linear decomposition method is used to decompose noise and improve the signal-to-noise ratio. The test results show that when the window length is greater than 10 days, both the fitted value and the residual value can achieve good stability. Using the six-year data of Beijing GNSS Network, after the data preparation of detrending, de-mutation, and deinterference, the sliding linear decomposition is performed on the window for 12 days, and multiple time series such as common mode noise, self-noise, and fitting value are calculated. A preliminary analysis of these sequences shows the low-passivity of the linear decomposition method, the consistency of common mode noise, and the difference in the station’s own noise. The results also show that the standard deviation of the fitted sequence is reduced to two-thirds of the original sequence. The fitted value time series is the main object of earthquake monitoring research, and the organic combination of multiple time series can be decomposed to meet different needs. 北京市 GNSS 连续观测台网范围小、土层站多、地壳运动水平低、噪声水平高，不利于地震监测的因素较多。本文用突变、连续光滑、共有噪声、测站自身噪声来分解测站位置的时间序列。基于连续光滑变化可线性拟合的特点，用短期线性分解法，分解出噪声，提高了信噪比。试验结果表明，当窗长大于 10 日时，拟合值和残差值都能取得很好的稳定性。用北京台网六年数据，经去趋势、去突变、去干扰等数据准备后，由窗长 12 日进行滑动短期线性分解，算得共有噪声、自身噪声、拟合值等多种时间序列，对这些序列的初步分析，显示了短期线性分解法的低通性、共有噪声的一致性、测站自身噪声的差异性，拟合值序列的标准差和幅差减小到分解前的三分之二左右。拟合值时间序列是地震监测研究的主要对象，分解得到多种时间序列的有机组合可满足不同需求。
• DOI: https://doi.org/10.35534/go.0204016
• Cite: 吴培稚，胡乐银，赵桂儒，等．北京 GNSS 地震监测用时间序列生成的试验研究［J］．测绘观察， 2020，2（4）：127-137．