GNSS deformation monitoring analysis based on the spatio-temporal Kalman filter: A comparison study

Kalman filter (KF) is a widely applied technique for deformation monitoring, which can estimate the deformation displacement from the noisy Global navigation satellite system (GNSS) measurements. This work compares the traditional KF and spatio-temporal Kalman filter (STKF) from the aspect of algorithm models and simulation results. The algorithm implementation of KF and STKF for deformation monitoring are given and analyzed in detail. In the case of stable deformation process, results show that both methods can accurately estimate the deformation displacement. In the case of sudden deformation process, such as burst step displacement and slope displacement, STKF outperforms KF via its spatio-temporal modelling. Based on the Kriging model, STKF can fully exploit the correlation among different monitoring points, then estimate the deformation without low delay.