Kalman filter for integration of GNSS and InSAR data applied for monitoring of mining deformations

Abstract

[EN] Ground deformation monitoring can be performed using different measurement methods, e.g., leveling, gravimetry, photogrammetry, laser scanning, satellite navigation systems, Synthetic Aperture Radar (SAR), and others. In the presented study we introduced an original methodology of integration of the Differential Satellite Interferometric SAR (DInSAR) and Global Navigation Satellite Systems (GNSS) data using Kalman filter. However, technical problems related to invalid GNSS receivers functioning and noisy DInSAR results have a great impact on calculations provided only in the forward Kalman filter mode. To reduce the impact of unexpected discontinuity of observations, a backward Kalman filter was also introduced. The applied algorithm was tested in the Upper Silesian coal mining region in Poland. The paper presents the methodology of DInSAR and GNSS integration appropriate for small-scale and non-linear motions. The verification procedure of the obtained results was performed using an external data source – GNSS campaign measurements. The overall RMS errors reached 18, 16, and 42 mm for the Kalman forward, and 19, 17, and 44 mm for the Kalman backward approaches in North, East, and Up directions, respectively.