Establishment Of Three-Dimensional Surface Deformation Field By GPS-InSAR Data Fusion

Geological hazards often have great destructive power,and China is a country with serious geological hazards.Therefore,the importance of research and prevention of geological hazards has become increasingly prominent.GPS and InSAR technology have become increasingly mature and efficient means of geological hazard monitoring.According to the complementary advantages of the two technologies,GPS-InSAR data fusion can effectively improve the errors that InSAR data itself is difficult to eliminate,and can effectively integrate the high temporal resolution and high plane position accuracy of GPS technology with the high spatial resolution and high altitude deformation accuracy of InSAR technology.However,how to efficiently fuse the two types of data has been a hot topic for scholars at home and abroad.For the related algorithms of GPS-InSAR data fusion,this paper does the following research:1.Establishment of GPS-InSAR data fusion model with double constraints of stochastic model and functional model.InSAR technology can only acquire one-dimensional surface deformation of radar pulse incidence direction because of LOS ambiguity,which can not satisfy the quantitative description of three-dimensional surface deformation.Even if the LOS direction measurements of multi-orbits are obtained,the results of three-dimensional deformation can not be obtained satisfactorily in general because of the great difference of geometric imaging.Moreover,InSAR technology is insensitive to the North-South deformation information of monitoring points.Therefore,in order to solve the above problems,this paper establishes a deformation model with additional stochastic model constraints based on GPS monitoring results as prior information,and takes the North-South information monitored by GPS as a strong constraint condition for North-South deformation,and establishes a Dual-constrained GPS-InSAR model with stochastic model and functional model for data fusion.The reliability and practicability of the model are verified by simulation experiments and Xi'an measured data.The results show that the model effectively improves the accuracy of ENU direction calculation.2.Adaptive Bayes variance component estimation based on posterior estimation of stochastic model is used to solve three-dimensional deformation field.In GPS-InSAR data fusion,the unreasonable allocation of weights of different observation values will directly affect the accuracy of the final solution of three-dimensional deformation information.In order to balance the weights of InSAR information and prior GPS information,a functional model based on Bayes statistical theory is established with high precision GPS observation as prior information and LOS deformation as observation information.The adaptive Bayes variance component estimation is applied to Bayes estimation.The adaptive Bayes variance component estimation is constructed,and the weights of GPS prior information and LOS direction observation information are adjusted reasonably.At the same time,Resist the possible gross errors in LOS direction.The experimental data in Xi'an area are used to verify the validity of the method.The results show that the method can effectively improve the accuracy of the three-dimensional deformation field.3.Inversion of Co-seismic Slip Distribution of Wenchuan Mw7.9 Earthquake Based on High Precision Deformation Field.The three-dimensional deformation field of Wenchuan earthquake is calculated by using GPS-InSAR fusion model with double constraints of function model and stochastic model,which is used as surface deformation constraints.The co-seismic slip distribution of Wenchuan earthquake is inverted by combining the geometric model of sectional faults.Compared with GPS inversion results,the inversion results of GPS-InSAR fusion data have better continuity,relatively concentrated slip distribution and more fine slip distribution.In order to verify the reliability of slip distribution inversion results,forward validation is carried out by using the inversion results of GPS-InSAR fusion data.The forward results are in good agreement with the measured GPS data.