SAR tomography optimization by interior point methods via atomic decomposition—The convex optimization approach

---

In the Multi-Baseline SAR tomography remote sensing technique, the tomographic resolution is proportional to the vertical aperture component of the synthetic antenna.
In order to avoid the problem of obtaining aliased tomographic results when designing multi-baseline SAR acquisition geometries using the fewest number of repeated radar tracks, it is necessary to process the data-set by advanced signal processing techniques that can properly process coherent and distributed composed environments SAR data.
In this paper the Digital Gabor Transform (DGT) decomposition for sparsity seeking and the Compressed Sensing (CS) for signal recovery techniques performance will be analyzed. Recovery in highly over-complete dictionaries leads to large-scale optimization problems that can be successfully reached specially because of recent advances in linear and quadratic programming by Interior Point Methods …

link to full text: SAR TOMOGRAPHY OPTIMIZATION BY INTERIOR POINT METHODS VIA ATOMIC DECOMPOSITION - THE CONVEX OPTIMIZATION APPROACH

More pubblications at:
https://scholar.google.com/citations?user=GVyeIgIAAAAJ

---