张菊清, 郝蓉, 张勤, 聂建亮. 基于各向异性协方差函数的自适应拟合推估[J]. 武汉大学学报 ( 信息科学版), 2014, 39(10): 1179-1183.
引用本文: 张菊清, 郝蓉, 张勤, 聂建亮. 基于各向异性协方差函数的自适应拟合推估[J]. 武汉大学学报 ( 信息科学版), 2014, 39(10): 1179-1183.
ZHANG Juqing , HAO Rong, ZHANG Qin, NIE Jianliang. Adaptive  Collocation Based on Anisotropic  Covariance Function[J]. Geomatics and Information Science of Wuhan University, 2014, 39(10): 1179-1183.
Citation: ZHANG Juqing , HAO Rong, ZHANG Qin, NIE Jianliang. Adaptive  Collocation Based on Anisotropic  Covariance Function[J]. Geomatics and Information Science of Wuhan University, 2014, 39(10): 1179-1183.

基于各向异性协方差函数的自适应拟合推估

Adaptive  Collocation Based on Anisotropic  Covariance Function

  • 摘要: 随机信号协方差函数的拟合和确定是拟合推估的关键 在常规协方差函数拟合时通常假定随机信号为具有各向同性的随机过程而事实上各向异性更具有普遍性 结合方差在不同方向的误差分量表达式给出了各向异性协方差函数的拟合方法利用由方差分量估计构建的自适应因子调节观测随机误差与信号对模型参数估计的贡献以减弱观测误差和随机信号先验模型不确定而带来的影响并将其应用于InSAR监测缺失数据填补中 计算结果表明拟合推估具有较好的缺失数据填补能力应用基于各向异性协方差函数的自适应拟合推估其填补精度得到进一步的改善.

     

    Abstract: Covariance function  fittin g for  stochastic  si gnal  is  a key problem for  collocation.In  theprocess  of  covariance  function estimation we often  assume  stochastic  si gnals with the  characteristic of isotro pic but anisotropic  is more generall y.Combined the  expressions  of  error  component  in different directionsa method of  covariance  function  fittin g based on anisotropic  is  given.Further adaptive collocation which constructed by variance  component  estimations  can ad just  the  contribution  to model parameters  by observation errors  and stochastic  si gnals and weaken the  affect  leadin g by their  uncertaint yis  proposed and applied  in missing InSAR data  fittin g.A practical  example  shows  that  collocation  can well supply the missing dataand adaptive  collocation based on anisotropic  covariance  function  can give  hi gher accurac y in missing data  fittin g.

     

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