基于各向异性协方差函数的自适应拟合推估

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.

Adaptive Collocation Based on Anisotropic Covariance Function

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．