融合GPS数据的PSDInSAR公用主影像的优化选取

Method for Optimum Selection of Common Master Acquisition for PS-DInSAR Fusing GPS Data

分析了永久散射体合成孔径雷达差分干涉测量(PS-DInSAR)引起相干性损失的主要影响因子,提出一种顾及大气延迟变化差异的PS-DInSAR公用主影像的优化选取方法,给出了具体的函数模型、建模思想及求解方法.借助天津地区欧空局ENVISAT(environmental satellite)卫星ASAR(advanced synthetic aperture radar)影像和连续运行GPS(global positioning system)永久监测站数据为源数据,采用Bernese 5.0和Matlab7.1及Shell自编程序等开展了融合GPS数据的公用主影像的优化选取实验.实验结果表明,融合GPS数据的模型相关系数法能准确快速地从多幅SAR影像中选出最优公用主影像,为PS-DInSAR的高精度形变监测奠定了基础.

An analysis was made of the major factors causing loss of correlation in permanent scatterer synthetic aperture radar differential interferometry.A method considering atmospheric delay variety differences was adopted to optimally select the common master image for PSDInSAR.Its specific function model,modeling principle and solution were provided.The original data came from continuous GPS permanent station and ENVISAT satellite ASAR images in Tianjin area from European Space Agency.Based on Bernese 5.0,Matlab7.1 and Shell programs,a test is made on the optimum selection of common master image fusing GPS data.The experiment shows the model correlation coefficient method fusing GPS data can select the optimal common master image from many SAR images rapidly and correctly,which guarantees the high-precision of PSDInSAR deformation survey.