EGU General Assembly 2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.

Noise correction and integration of HR-GNSS and seismological data for small earthquakes

Iwona Kudłacik and Jan Kapłon
Iwona Kudłacik and Jan Kapłon
  • Wrocław University of Environmental and Life Sciences, Institute of Geodesy and Geoinformatics, Wrocław, Poland (

High-rate GNSS (HR-GNSS) observations are used for high-precision applications, where the point position changes in short intervals are required, such as earthquake analysis or structural health monitoring. We aim to apply the HR-GNSS observations into mining tremors monitoring, where the dynamic displacement amplitudes reach maximally dozens of millimetres. The study contains the analysis of several mining tremors of magnitudes 3-4 in Poland, recorded within the EPOS-PL project.

The HR-GNSS position is obtained with over 1 Hz frequency in kinematic mode with relative or absolute approaches. For short periods (up to several minutes), the positioning accuracy is very high, but the displacement time series suffer from low-frequency fluctuations. Therefore, it is not possible to apply them directly in the analysis of seismic phenomena, thus it is necessary to filter out low- and high-frequency noise.

In this study, we discussed some methods that are useful to reduce the noise in HR-GNSS displacement time series to obtain precise and physically correct results with reference to seismological observations, which for dynamic position changes are an order of magnitude more accurate. We presented the band-pass filtering application with automatic filtration limits based on occupied bandwidth detection and the discrete wavelet transform application with multiresolution analysis. The correction of noise increases the correlation coefficient by over 40%, reaching values over 0.8. Moreover, we tested the application of the basic Kalman filter to the integration of sensors: HR-GNSS and an accelerometer to visualize the most actual displacements of the station during a small earthquake - a mining tremor. The usefulness of this algorithm for the assumed purpose was confirmed. This algorithm allows to reduce the noise from HR-GNSS results, and on the other hand, to minimize the potential seismograph drift and its errors caused by the limited dynamic range of the seismograph. An unquestionable advantage is the possibility of obtaining a time series of displacements with a high frequency (equal to the frequency of seismograph observations, e.g. 250 Hz) showing the full range of station motion: dynamic and static displacements caused by an earthquake.

How to cite: Kudłacik, I. and Kapłon, J.: Noise correction and integration of HR-GNSS and seismological data for small earthquakes, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-8811,, 2021.