Analysis of the dynamic behavior of structures using the high-rate GNSS-PPP method combined with a wavelet-neural model: Numerical simulation and experimental tests

Recently, the high rate global navigation satellite system-precise point positioning (GNSS-PPP) technique has been used to detect the dynamic behavior of structures. This study aimed to increase the accuracy of the extraction oscillation properties of structural movements based on the high-rate (10?Hz) GNSS-PPP monitoring technique. A developmental model based on the combination of wavelet package transformation (WPT) de-noising and neural network prediction (NN) was proposed to improve the dynamic behavior of structures for GNSS-PPP method. A complicated numerical simulation involving highly noisy data and 13 experimental cases with different loads were utilized to confirm the efficiency of the proposed model design and the monitoring technique in detecting the dynamic behavior of structures. The results revealed that, when combined with the proposed model, GNSS-PPP method can be used to accurately detect the dynamic behavior of engineering structures as an alternative to relative GNSS method.     

Displacement monitoring performance of relative positioning and Precise Point Positioning (PPP) methods using simulation apparatus

Besides the classical geodetic methods, GPS (Global Positioning System) based positioning methods are widely used for monitoring crustal, structural, ground etc., deformations in recent years. Currently, two main GPS positioning methods are used: Relative and Precise Point Positioning (PPP) methods. It is crucial to know which amount of displacement can be detected with these two methods in order to inform their usability according to the types of deformation. Therefore, this study conducted to investigate horizontal and vertical displacement monitoring performance and capability of determining the direction of displacements of both methods using a developed displacement simulator apparatus. For this purpose, 20 simulated displacement tests were handled. Besides the 24?h data sets, 12?h, 8?h, 4?h and 2?h subsets were considered to examine the influence of short time spans. Each data sets were processed using GAMIT/GLOBK and GIPSY/OASIS scientific software for relative and PPP applications respectively and derived displacements were compared to the simulated (true) displacements. Then statistical significance test was applied. Results of the experiment show that using 24?h data sets, relative method can determine up to 6.0?mm horizontal displacement and 12.3?mm vertical displacement, while PPP method can detect 8.1?mm and 19.2?mm displacements in horizontal and vertical directions respectively. Minimum detected displacements are found to grow larger as time spans are shortened.