基于平滑样条的PSInSAR大气效应分离研究

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

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。

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-pre- cision, surface deformation monitoring results. As the main error source in InSAR ,atmospheric sig- nals 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 un- wrapped 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 spec- trum of various contributing factors will overlap, and the classic filter is powerless. This paper propo- ses methodologies which can automatically choose a smoothing parameter based on a fast robust ver- sion of a discrete smoothing spline instead of classic filter to effectively separate the phase compo- nents.