Conventional Interferometric Synthetic Aperture Radar(InSAR) technology can only measure one-dimensional surface displacement(along the radar line-of-sight(LOS) direction).Here we presents a method to infer three-dimensional surface displacement field by combining SAR interferometric phase and amplitude information of ascending and descending orbits.The method is realized in three steps:(1) measuring surface displacements along the LOS directions of both ascending and descending orbits based on interferometric phases;(2) measuring surface displacements along the azimuth directions of both the ascending and descending orbits based on the SAR amplitude data;and(3) estimating the three-dimensional(3D) surface displacement field by combining the above four independent one-dimensional displacements using the method of least squares and Helmert variance component estimation.We apply the method to infer the 3D surface displacement field caused by the 2003 Bam,Iran,earthquake.The results reveal that in the northern part of Bam the ground surface experienced both subsidence and southwestward horizontal movement,while in the southern part uplift and southeastward horizontal movement occurred.The displacement field thus determined matches the location of the fault very well with the maximal displacements reaching 22,40,and 30 cm,respectively in the up,northing and easting directions.Finally,we compare the 3D displacement field with that simulated from the Okada model.The results demonstrate that the method presented here can be used to generate reliable and highly accurate 3D surface displacement fields.
HU JunLI ZhiWeiZHU JianJunREN XiaoChongDING XiaoLi
Although the modified Goldstein filter based on the local signal-to-noise （SNR） has been proved to be superior to the classical Goldstein and Baran filters with more comprehensive filter parameter, its adaptation is not always sufficient in the reduction of phase noise. In this work, the local SNR-based Goldstein filter is further developed with the improvements in the definition of the local SNR and the adaption of the filtering patch size. What＇s more, for preventing the loss of the phase signal caused by the excessive filtering, an iteration filtering operation is also introduced in this new algorithm. To evaluate the performance of the proposed algorithm, both a simulated digital elevation model （DEM） interferogram and real SAR deformation interferogram spanning the L＇ Aquila earthquake are carried out. The quantitative results from the simulated and real data reveal that up to 79.5% noises can be reduced by the new filter, indicating 9%-32% improvements over the previous local SNR-based Goldstein filter. This demonstrates that the new filter is not only equipped with sufficient adaption, but also can suppress the phase noise without the sacrifice of the phase signal.
SUN QianLI Zhi-weiZHU Jian-junDING Xiao-liHU JunXU Bing
