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A Study Of GPS Dynamic Deformation Monitoring Data Processing Based On EMD And ICA

Posted on:2012-03-18Degree:MasterType:Thesis
Country:ChinaCandidate:F X LuoFull Text:PDF
GTID:2120330335490641Subject:Cartography and Geographic Information Engineering
Abstract/Summary:PDF Full Text Request
With a high degree of automation, can directly measure three-dimensional coordinates of monitoring points, without limit of climatic conditions and ventilation conditions and other characteristics, GPS has irreplaceable advantages in the dynamic deformation monitoring, and gradually applied. However, affected by the multipath error and the residual impact of tropospheric delay error, the accuracy of GPS dynamic measurement is still difficult to meet the requirements of the high accuracy dynamic deformation monitoring. Using the modern signal processing to process the GPS dynamic measurement data sequence and extract deformation information is an important way to solve this problem. Therefore, this paper first summarizes the data processing method of structural deformation monitoring. The capacity of denoising and Multi-scale with wavelet transform and empirical mode decomposition are researched. For the problem of dis-separating for the same frequency mixed signal with traditional data processing methods, while the frequency of multipath effects and low-frequency of structure vibration are mixed, the ICA for data processing in GPS dynamic deformation monitoring is deeply discussed, and utilized the sidereal day repeatability of multipath errors, the EMD-ICA method with reference signal is proposed. The specific research work and achievements are as follows:1. Systemly Overview the background and development status of GPS deformation monitoring, focus on reviewing some of the data processing method status about GPS dynamic deformation monitoring. At last, the advantages and disadvantages of these methods are summarized and analyzed.2. The simulated data and GPS data collected from the table test are used to test the ability of EMD and wavelet in signal denoising and multi-scale decomposition. The following are the conclusions from these tests:Both of EMD and Wavelet transform are good at extracting the deformation information. However, when the data is heavy noised, the stability of wavelet is better than EMD in denoising and multi-scale decomposition. While the EMD is adaptive method based on the data itself, and free to choose the wavelet base and the number of decompose layer.3. The EMD filtering method based on the cross-validation is developed. Experiments with both simulated data and real GPS observations shows that the method can select the signals in the IMFs, reduce random error and separate noise from signals adaptively. And it can be better for data filter denoising of dynamic deformation monitoring.4. The application of ICA in data processing of deformation Monitoring is discussed by the ICA simulation experiments with frequency mixing Signals. The following are the conclusions:Under the assumption of the signal are independence, ICA can effectively separate the mixed signals from the observed signals. It is illustrated that ICA is a suitable method of deformation information extraction when the frequency of the error signal and Deformation signal are mixed.5. As in the GPS dynamic deformation monitoring, the Frequency Range of multipath effects is large, it may mix with the low-Frequency of Vibration signals. What is more, the repeatability of sidereal day gradually reduced over time. The EMD-ICA method with reference signal to undermine the effects of multipah was proposed. Simulation test and practical application results show the effectiveness of this method.
Keywords/Search Tags:GPS, Dynamic deformation monitoring, Multipath effects, Empirical Mode Decomposition (EMD), Independent component analysis (ICA)
PDF Full Text Request
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