基于平滑样条的PSInSAR大气效应分离研究

永久散射体技术（permanent scatterers interferometric synthetic aperture radar，PSInSAR）通过提取时间维高相干点，根据各类信息的时空统计特性实现PS（persistent scatterers）点相位分量的分离，获得高精度地表形变监测结果。大气效应作为影响干涉测量精度的最主要误差源，可以通过经典滤波器分别在时间维和空间维滤波处理予以消除。在StaMPS（stanford method for persistent scatterers）技术体系中，大气效应分离时还保有全部的沉降信息。当地表形变速率较大时，大气效应和沉降信息的频谱重合度较高，经典滤波器无法将二者有效分离。通过平滑样条滤波分离大气效应和形变信息，采用广义交叉验证方法获取形变信息的最优估计值，可抗拒解缠错误引起的相位跳变干扰。最后根据模拟数据和ASAR（advanced synthetic aperture radar）数据对比分析高斯滤波和平滑样条滤波分离大气效应的效果，验证平滑样条方法的有效性。

Estimation of Atmospheric Phase Contributions Using Smoothing Spline in Persistent Scatterers Radar Interferometry

The PSInSAR technique can achieve separation of PS phase components, by extracting the time-dimensional PS points based on various temporal and spatial statistical properties to get high-precision, surface deformation monitoring results. As the main error source in InSAR, atmospheric signals can be isolated from the other components of the residual phase by classical filters in the spatial and temporal domains. Optionally, after 3D unwrapping, high-pass filtering can be applied to unwrapped data in time followed by a low-pass filter in space in order to remove the remaining spatial correlated errors (atmosphere and orbit errors). Thus, when the deformation rate is large, the spectrum of various contributing factors will overlap, and the classic filter is powerless. This paper proposes methodologies which can automatically choose a smoothing parameter based on a fast robust version of a discrete smoothing spline instead of classic filter to effectively separate the phase components.