Linear and adaptive spaceborne three-dimensional SAR tomography: a comparison on real data

Three-dimensional (3-D) synthetic aperture radar (SAR) imaging is a recent technique, based on coherent SAR data combination, and aims to obtain a full 3-D analysis in space. It is a multibaseline extension of the SAR interferometry concept and offers new options for the analysis and monitoring of ground scenes by means of the capability of separating the scattering phenomena along the height dimension. In this work, the authors summarise and extend the results obtained by processing real ERS satellite urban data characterised by a long time span of acquisition and non-uniformly spaced satellite passes, comparing the performance in height focusing obtained with a singular value decomposition (SVD)-based method and adaptive beamforming.