Investigation of the noise properties at low frequencies in long GNSS time series
Investigation of the noise properties at low frequencies in long GNSS time series
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研究长 GNSS 时间序列低频噪声特性
DOI：
10.1007/s00190-019-01244-y
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发表时间：
2019-09-01
影响因子：
4.4
通讯作者：
Fernandes, R. M. S.
中科院分区：
文献类型：
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作者：
He, X.;Bos, M. S.;Fernandes, R. M. S.
根据 GNSS 时间序列估算速度的精度主要取决于低频噪声（低于 0.2-0.1 cpy），这些噪声通常由幂律模型描述。由于 GNSS 观测记录已经有二十多年了，有关这些低频噪声的新信息已经可用，我们研究是否应使用对数似然、Akaike 和贝叶斯信息标准考虑替代噪声模型。使用 110 个全球分布的 IGS 站并进行至少 12 年的观测，我们发现其中 80-90% 的首选噪声模型仍然是幂律或带有白噪声的闪烁噪声。对于大约 6% 的站点，我们发现存在随机游走噪声，当考虑到时间序列的随机噪声模型时，线性趋势不确定性增加了约 1.5 至 8.4 倍，这与之前的研究一致。接下来，具有白噪声的广义高斯-马尔可夫模型分别更好地描述了东部和北部分量的 4% 和 5% 的站点以及垂直分量的 13% 的随机属性。对于这些站，与使用标准幂律加白噪声模型的情况相比，与构造速率相关的不确定性大约小 2 倍。
The accuracy by which velocities can be estimated from GNSS time series is mainly determined by the low-frequency noise, below 0.2-0.1 cpy, which are normally described by a power-law model. As GNSS observations have now been recorded for over two decades, new information about the noise at these low frequencies has become available and we investigate whether alternative noise models should be considered using the log-likelihood, Akaike and Bayesian information criteria. Using 110 globally distributed IGS stations with at least 12 years of observations, we find that for 80-90% of them the preferred noise models are still the power law or flicker noise with white noise. For around 6% of the stations, we found the presence of random-walk noise, which increases the linear trend uncertainty when taken into account in the stochastic noise model of the time series by about a factor of 1.5 to 8.4, in agreement with previous studies. Next, the Generalised Gauss-Markov with white noise model describes the stochastic properties better for 4% and 5% of the stations for the East and North component, respectively, and 13% for the vertical component. For these stations, the uncertainty associated with the tectonic rate is about 2 times smaller compared to the case when the standard power-law plus white noise model is used.