SAR Interferometry And Tomography Based On Repeat-pass Spaceborne Platforms For Applications Of Urban Area

With the rapid developing economies and the accelerating urbanization,the urban population grows quickly.It is of great importance for city health to acquire 3-D urban model and to conduct dynamic monitoring over urban areas.With the development of spaceborne radar technique,especially after the launches of modern SAR systems(e.g.Terra SAR-X and Cosmo-Sky Med),the applications of SAR technique have been widely extended.The characteristics of the new generation of spaceborne systems rely on the higher spatial resolution and orbit accuracy,which dramatically facilitates the urban appli-cation of 3-D reconstruction and dynamic monitoring via repeat-pass SAR interferometry and tomography.Taking advantage of the observations over the same scene on slightly different viewing angles and/or various times,In SAR can estimate the elevation and deformation from the phase differences caused by different path delays.Despite its wide applications on to pography reconstruction and deformation monitoring,conventional In SAR suffers from the errors of phase unwrapping,orbit and DEM and the incapability of long time deformation measurements,which can be overcome by the repeated observations over the same area,called multitemporal In SAR(MT-In SAR).In addition,based on the single strong scatterer assumption and the phase-information-only usage,In SAR fails to recon-struct the scattering profiles.As the expansion of In SAR,SAR tomography(Tomo SAR)makes use of both amplitude and phase,and it forms another aperture normal to slant range(NSR),thus possessing real 3-D imaging capability.Despite the superiorities of repeat-pass MT-In SAR and Tomo SAR over conventional In SAR,there are problems that need urgent solutions.MT-In SAR faces the uncertainties of parameter estimation and phase unwrapping,and Tomo SAR fails to reach the trade-off of superresolution and constant false alarm rate(CFAR),and the performance and efficiency.Aimed at dealing with the above problems,based on repeat-pass spaceborne SAR,this paper does research on In SAR and Tomo SAR techniques,listed as follows.1.In the framework of single-master image MT-In SAR,PS-In SAR has been mod-ified and improved.The PS-In SAR technique is well suited for urban area processing as the large number of permanent scatterers in man-made constructions.The referenced network(RN)is constructed by region growing method,which ensures the connectivity,coverage and reliability.The parameter estimation of the remaining points has been conducted via weighted multi-referenced points in the afore-constructed RN,which reduces the risks of possible errors and improves the reliability.In the same time,the use of temporal coefficient for PS confirmation has been validated versus the number of SLCs,and the possible seasonal deformation has been analyzed.2.In the regime of multimaster MT-In SAR,a baseline linear combination(BLC)algorithm has been proposed,overcoming the phase unwrapping problems in areas where DEM sharply varies,especially in urban areas with highrise buildings,and DEM with high resolution and high accuracy has been been generated.BLC approach generates interferograms with nearly zero baselines so as to minimize the effects of the uncertainties in the DEM used.It incorporates the baseline combination method with adjacent gradient networking to successfully unwrap the interferograms even in abruptly discontinuous areas,which in turn can be used to estimate a highresolution DEM and offers reliable information for later displacement estimation.In the same time,analysis on the interfer-ogram formation,the outlier detector and possible noise sources has been conducted.3.When studying repeat-pass Tomo SAR,two algorithms about imaging and detection have been proposed,namely CS-GLRT and iterative-SGRLT.Urban tomography focuses on the layover separation and scattering profile reconstruction.The modern space-borne SAR may lead to severe layover phenomenon,which requires imaging methods with super-resolution.However,the now available method,such as SL1MMER,fails to control false alarm rate(CFAR).CS-GLRT is proposed to achieve the super resolu-tion and CFAR.In the first step,an L1-norm minimization is carried out to give a robust estimation of the candidate positions pixel by pixel with super-resolution.In the second step,a multiple hypothesis test is implemented by the generalized likelihood ratio test(GLRT)to achieve model order selection,where the mapping matrix is constrained within the afore-selected columns,namely,within the candidate positions,and the parameters are estimated by least square(LS)method.Experimental results show its capability of separating the closely located scatterers with a quasiconstant false alarm rate(QCFAR),as well as of obtaining an estimation accuracy approaching Cramer Rao Low Bound(CRLB),and this method is especially suitable for urban areas with very dense infrastructure and man-made buildings.Nevertheless the superiority of super-resolution imaging method,its application has been great hindered by its heavy computation burden?and the performance of some fast methods are far from satisfactory.To handle these problems,iterative-SGLRT has been proposed.In the technique,the number of scatterers is sequentially decided by GLRT pixel by pixel,after iteratively estimating the parame-ters.It transfers the multi-order optimal searching to multiple first-order searching,thus greatly reduces the computation burden with the performance ensured.It is a good trade off of the afore-proposed methods of supGLRT and fast-sup-GLRT on accuracy and efficiency.Iterative-SGLRT has been applied to the Terra SAR-X dataset over Shenzhen city.3D reconstruction of the test site and the separation of the overlaid scatterers have been achieved.Also,verification using Li DAR indicated an RMSE of 0.1?_sof the height estimated.Accordingly,iterative-SGLRT is very suitable for large urban area processing for its superresolution,high efficiency,and robustness.