Stability Analysis of Deformation-Monitoring Network Points Using Simultaneous Observation Adjustment of Two Epochs

An important issue in deformation analysis is identification of (un)stable points in a monitoring network. This paper proposes a new method that identifies the unstable points of a network based on the generalized likelihood ratio (GLR) test. The method, which simultaneously uses the observations of two epochs, is called the simultaneous adjustment of two epochs (SATE) method. The existing methods apply individual least-squares adjustment to the observations of each epoch. SATE is applicable to one-, two-, or three-dimensional deformation networks with any type of observations, including distances, angles, global positioning system (GPS) baselines, and height difference. To investigate the performance of the proposed method, observations of a real GPS deformation-monitoring network were used. The results for unstable points identification are identical to those of the existing methods. Furthermore, a few simulation case studies were used to evaluate the efficacy of the proposed method. The simulated results for the deformation-monitoring networks, with different scenarios, confirm that the proposed method always performs the best. This method can thus be introduced as a reliable method that provides results that are superior to those of the two existing classical methods.