Global Positioning System (GPS) is being actively applied to measure static and dynamic deformation. However, some error sources, such as multipath effects and receiver noise, affect the data quality of GPS deformation measurement. To obtain accurate positioning results by GPS, it is significant to mitigate the contamination of noise and outlier in the GPS observations and solutions. Therefore this paper intends to take an alternative data processing method to deal with dynamic deformation analysis. The combination of wavelet transform and empirical mode decomposition (EMD) method is adopted to analyze the measured deformation signal. Wavelet filter as a nonlinear process is very useful in reducing random noise, while EMD method has offered a powerful method for nonlinear and non-stationary data processing. In this research, firstly the outlier inside of the measured deformation signal is removed by wavelet transform. After comparison of the performances from different data processing approaches, the results indicate that the proposed EMD-based wavelet filtering method is more effective to deal with the dynamic deformation data processing, which can enhance the data quality of GPS measurement by denoising.
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