Matches in SemOpenAlex for { <https://semopenalex.org/work/W2093928871> ?p ?o ?g. }
Showing items 1 to 69 of
69
with 100 items per page.
- W2093928871 abstract "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 (IPM). This paper considers the Convex Optimization (CVX) tomographic solution in order to process multi-baseline datasets over forested environments, in a Fourier under-sampled configuration. In this situation, the vertical reflectivity function is in a smooth domain. The DGT is a suitable method in order to generate an over-complete dictionary for sparsity seeking. The CVX Second Order Cone Programming Solution (SOCPs) by IPM using a generic log-barrier algorithm has been tested in order to optimize the dictionary atoms. In particular the following recovery technique has been implemented: l1 norm minimization with quadratic constraints (L1QC). This technique has been validated over real forested areas pointing out the better performance of the proposed solution in such a particular environment." @default.
- W2093928871 created "2016-06-24" @default.
- W2093928871 creator A5045538421 @default.
- W2093928871 date "2014-07-01" @default.
- W2093928871 modified "2023-10-16" @default.
- W2093928871 title "SAR tomography optimization by Interior Point Methods via atomic decomposition — The Convex Optimization approach" @default.
- W2093928871 cites W1963753244 @default.
- W2093928871 cites W2009923109 @default.
- W2093928871 cites W2012110988 @default.
- W2093928871 cites W2018850201 @default.
- W2093928871 cites W2048289234 @default.
- W2093928871 cites W2103677830 @default.
- W2093928871 cites W2129638195 @default.
- W2093928871 cites W2145096794 @default.
- W2093928871 cites W2160396672 @default.
- W2093928871 cites W2204863336 @default.
- W2093928871 cites W2613211097 @default.
- W2093928871 cites W4250589301 @default.
- W2093928871 doi "https://doi.org/10.1109/igarss.2014.6946823" @default.
- W2093928871 hasPublicationYear "2014" @default.
- W2093928871 type Work @default.
- W2093928871 sameAs 2093928871 @default.
- W2093928871 citedByCount "9" @default.
- W2093928871 countsByYear W20939288712017 @default.
- W2093928871 countsByYear W20939288712019 @default.
- W2093928871 countsByYear W20939288712020 @default.
- W2093928871 countsByYear W20939288712021 @default.
- W2093928871 countsByYear W20939288712023 @default.
- W2093928871 crossrefType "proceedings-article" @default.
- W2093928871 hasAuthorship W2093928871A5045538421 @default.
- W2093928871 hasConcept C112680207 @default.
- W2093928871 hasConcept C11413529 @default.
- W2093928871 hasConcept C126255220 @default.
- W2093928871 hasConcept C137836250 @default.
- W2093928871 hasConcept C154945302 @default.
- W2093928871 hasConcept C157972887 @default.
- W2093928871 hasConcept C2524010 @default.
- W2093928871 hasConcept C33923547 @default.
- W2093928871 hasConcept C41008148 @default.
- W2093928871 hasConcept C81845259 @default.
- W2093928871 hasConcept C87360688 @default.
- W2093928871 hasConceptScore W2093928871C112680207 @default.
- W2093928871 hasConceptScore W2093928871C11413529 @default.
- W2093928871 hasConceptScore W2093928871C126255220 @default.
- W2093928871 hasConceptScore W2093928871C137836250 @default.
- W2093928871 hasConceptScore W2093928871C154945302 @default.
- W2093928871 hasConceptScore W2093928871C157972887 @default.
- W2093928871 hasConceptScore W2093928871C2524010 @default.
- W2093928871 hasConceptScore W2093928871C33923547 @default.
- W2093928871 hasConceptScore W2093928871C41008148 @default.
- W2093928871 hasConceptScore W2093928871C81845259 @default.
- W2093928871 hasConceptScore W2093928871C87360688 @default.
- W2093928871 hasLocation W20939288711 @default.
- W2093928871 hasOpenAccess W2093928871 @default.
- W2093928871 hasPrimaryLocation W20939288711 @default.
- W2093928871 hasRelatedWork W1571214415 @default.
- W2093928871 hasRelatedWork W1601283844 @default.
- W2093928871 hasRelatedWork W1987794367 @default.
- W2093928871 hasRelatedWork W2011094784 @default.
- W2093928871 hasRelatedWork W2023008490 @default.
- W2093928871 hasRelatedWork W2117781171 @default.
- W2093928871 hasRelatedWork W2189723018 @default.
- W2093928871 hasRelatedWork W3003165794 @default.
- W2093928871 hasRelatedWork W4287899549 @default.
- W2093928871 hasRelatedWork W165108556 @default.
- W2093928871 isParatext "false" @default.
- W2093928871 isRetracted "false" @default.
- W2093928871 magId "2093928871" @default.
- W2093928871 workType "article" @default.