Image alignment is a crucial step in synthetic aperture radar (SAR) interferometry. Interferogram formation requires images to be coregistered with an accuracy of better than a few tenths of a resolution cell to avoid significant loss of phase coherence. In conventional interferometric precise coregistration methods for full-resolution SAR data, a 2-D polynomial of low degree is usually chosen as warp function, and the polynomial parameters are estimated through least squares fit from the shifts measured on image windows. In case of rough topography or long baselines, the polynomial approximation may become inaccurate, leading to local misregistrations. These effects increase with spatial resolution of the sensor. An improved elevation-assisted image-coregistration procedure can be adopted to provide better prediction of the offset vectors. This approach computes pixel by pixel the correspondence between master and slave acquisitions by using the orbital data and a reference digital elevation model (DEM). This paper aims to assess the performance of this procedure w.r.t. the standard one based on polynomial approximation. Analytical relationships and simulations are used to evaluate the improvement of the DEM-assisted procedure w.r.t. the polynomial approximation as well as the impact of the finite vertical accuracy of the DEM on the final coregistration precision for different resolutions and baselines. The two approaches are then evaluated experimentally by processing high-resolution SAR data provided by the COnstellation of small Satellites for the Mediterranean basin Observation (COSMO/SkyMed) and TerraSAR-X missions, acquired over mountainous areas in Italy and Tanzania, respectively. Residual-range pixel offsets and interferometric coherence are used as quality figure. © 2006 IEEE. @en

Image alignment is without doubt the most crucial step in SAR Interferometry. Interferogram formation requires images to be coregistered with an accuracy of better than 1/8 pixel to avoid significant loss of phase coherence. Conventional interferometric precise coregistration methods for full-resolution SAR data (Single-Look Complex imagery, or SLC) are based on the cross-correlation of the SLC data, either in the original complex form or as squared amplitudes. Offset vectors in slant range and azimuth directions are computed on a large number of windows, according to the estimated correlation peaks. Then, a two-dimensional polynomial of a certain degree is usually chosen as warp function and the polynomial parameters are estimated through LMS fit from the shifts measured on the image windows. In case of rough topography and long baselines, the polynomial approximation for the warp function becomes inaccurate, leading to local misregistrations. Moreover, these effects increase with the spatial resolution and then with the sampling frequency of the sensor, as first results on TerraSAR-X interferometry confirm. An improved, DEM-assisted image coregistration procedure can be adopted for providing higher-order prediction of the offset vectors. Instead of estimating the shifts on a limited number of patches and using a polynomial approximation for the transformation, this approach computes pixel by pixel the correspondence between master and slave by using the orbital data and a reference DEM. This study assesses the performance of this approach with respect to the standard procedure. In particular, both analytical relationships and simulations will evaluate the impact of the finite vertical accuracy of the DEM on the final coregistration precision for different radar postings and relative positions of satellites. The two approaches are compared by processing real data at different carrier frequencies and using the interferometric coherence as quality figure.@en