Analysis of crustal deformation based on iterative solutions of Robust Least Squares Collocation

作者：Wang Le-Yang^*; Chen Han-Qing

来源：Acta Geophysica Sinica, 2017, 60(8): 3062-3071.

DOI：10.6038/cjg20170814

• Covariance function
• Robust fitting
• Median
• Median parameter
• Least squares collocation
• Outliers

The rationality of the results obtained by the least squares collocation(LSC) method in analysis of crustal deformation depends on the fitting of the empirical covariance function. The Robust Least Square Collocation method based on Observation Initial Median Values (RLSC-OIMV) and the Robust Least Square Collocation method based on Median Parameter (RLSC-MP) are proposed consdiering the observation data contains outliers. Firstly, the observation median value is used to obtain the initial weight matrix of observation data and the median parameters method is used to obtain the initial solution of least squares collocation in RLSC-OIMV and RISC-MP, respectively. With the initial parameters of covariance function, the equivalent weight scheme is then applied to obtain the robust parameters estimation of covariance function and least squares collocation solutions through iteration. We apply the two proposed methods and the traditional methods to analyze GPS vertical displacement data of the Lushan earthquake and the InSAR coseismic displacement data of the L'Aquila earthquake in Italy. The results show that the RLSC-OIMV is better and more robust than other methods.

• 出版日期2017-8