Tomography SAR (TomoSAR) methods recover the 3D structure of targets by processing several SAR images simultaneously. Depending on the degree of approximation, recovering the vertical structure can amount to a 1D problem (processing a vector of pixels), a 2D problem (processing a matrix) or a 3D problem (processing the whole 3D stack at once). The computational burden decreases from the 3D to the 1D, but the constraints for a proper reconstruction are tighter. Hence, this paper discusses the limit and criterion for the feasibility of each method. The huge computational burden of TomoSAR 3D method is addressed by a fast implementation on GPUs. Theoretical analyses and our approach are demonstrated on simulated data, as well as on real data from the ESA AlpTo-moSAR campaign.
Processing Options for High-Resolution SAR Tomography from Irregular Trajectories
Yu Y.;Tebaldini S.;Liao M.
2020-01-01
Abstract
Tomography SAR (TomoSAR) methods recover the 3D structure of targets by processing several SAR images simultaneously. Depending on the degree of approximation, recovering the vertical structure can amount to a 1D problem (processing a vector of pixels), a 2D problem (processing a matrix) or a 3D problem (processing the whole 3D stack at once). The computational burden decreases from the 3D to the 1D, but the constraints for a proper reconstruction are tighter. Hence, this paper discusses the limit and criterion for the feasibility of each method. The huge computational burden of TomoSAR 3D method is addressed by a fast implementation on GPUs. Theoretical analyses and our approach are demonstrated on simulated data, as well as on real data from the ESA AlpTo-moSAR campaign.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
