XIE Xilin, XU Caijun, WEN Yangmao, ZHOU Lixuan. A Refined Least Squares Collocation Method Based on Multiquadric Function[J]. Geomatics and Information Science of Wuhan University, 2018, 43(4): 592-598. DOI: 10.13203/j.whugis20150664
Citation: XIE Xilin, XU Caijun, WEN Yangmao, ZHOU Lixuan. A Refined Least Squares Collocation Method Based on Multiquadric Function[J]. Geomatics and Information Science of Wuhan University, 2018, 43(4): 592-598. DOI: 10.13203/j.whugis20150664

A Refined Least Squares Collocation Method Based on Multiquadric Function

Funds: 

The National High-Tech Research and Development Program of China (863 Program) 2013AA122501-3

the Special Earthquake Industry Research Project 201308009

the National Natural Science Foundation of China 41431069

the National Natural Science Foundation of China 41574002

the National Natural Science Foundation of China 41721003

the National Natural Science Foundation of China 41774011

More Information
  • Author Bio:

    XIE Xilin, master, specializes in the theories and methods of Geophysical Geodesy.xlxie@whu.edu.cn

  • Corresponding author:

    WEN Yangmao, PhD, associate professor.E-mail:ymwen@sgg.whu.edu.cn

  • Received Date: March 05, 2016
  • Published Date: April 04, 2018
  • Trend removal is the most common approach in conventional least squares collocation (LSC) to deal with nonstationarity. Due to the inaccuracy of the trend model, conventional LSC can barely eliminate the drift component of the data that results in estimation bias of the local covariance function and error of the interpolation values. Here we present a refined LSC method to estimate the drift component of the field and compensate the residualfrom LSC. The refined method employs the mulitiquadric function to approach the drift and the collocation to estimate signals. We apply the refined method to a synthetic data set and coseismic displacement data from the 2009 L'Aquila, Italy earthquake, and compare the results of refined method with conventional methods. The statistical results of residuals indicate that the refined method can achieve a more accurate result than conventional methods and is affected less by the observation distribution.
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