Name
Abstract | ||
|---|---|---|
This paper presents a study on the origin of the dominating scattering mechanisms observed in polarimetric synthetic aperture radar (SAR) images of ships. The study has been made by using numerical simulations, which have been carried out with a radar cross section (RCS) prediction tool (GRaphical Electromagnetic COmputing) and a SAR simulator. Extensive series of simulations has been run for realistic 3-D geometrical models of ships with various sizes. Different radar parameters, aspect angles, and sea surface states have been considered in the scenario. Data analysis with coherent target decompositions has indicated characteristic polarimetric signatures for particular ships within a specific range of viewing angles. This happens at highly oblique incidences where the responses appear to be less sensitive to changes in the operating frequency and bearing angles. Under such conditions, ship scattering can be schematized by the distribution of a set of guide scatterers with high RCS. Their positions and polarimetric characteristics are quantitatively summarized in a new feature vector, which has been proposed to be the basis for classification algorithms. Key ideas about this vector are presented at the end of this paper, jointly with some examples related to three different ships. Recent publications have shown that they can be successfully cast within a new unsupervised vessel classification scheme. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1109/TGRS.2008.2008443 | Geoscience and Remote Sensing, IEEE Transactions |
Keywords | Field | DocType |
electromagnetic wave scattering,inverse problems,physics computing,radar imaging,radar polarimetry,radar target recognition,remote sensing by radar,ships,synthetic aperture radar,Graphical Electromagnetic Computing,POLSAR ship imaging,SAR simulator,classification algorithms,polarimetric synthetic aperture radar,radar cross section prediction tool,scattering mechanism,ship polarimetric signature,ship radar scattering,simulated inverse SAR imagery,target decomposition,unsupervised vessel classification scheme,vessel scattering,Coherent target decompositions (CTDs),SAR polarimetry,polarimetric synthetic aperture radar (SAR) interferometry,vessel identification | Radar,Computer vision,Radar imaging,Feature vector,Polarimetry,Synthetic aperture radar,Remote sensing,Inverse synthetic aperture radar,Inverse problem,Artificial intelligence,Radar cross-section,Mathematics | Journal |
Volume | Issue | ISSN |
47 | 4 | 0196-2892 |
Citations | PageRank | References |
5 | 0.61 | 23 |
Authors | ||
6 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Gerard Margarit | 1 | 98 | 10.55 |
| Jordi J. Mallorqui | 2 | 247 | 25.70 |
| Joaquim Fortuny-Guasch | 3 | 74 | 11.12 |
| Carlos Lopez-Martinez | 4 | 210 | 29.10 |
| Fortuny-Guasch, J. | 5 | 5 | 0.61 |
| Lopez-Martinez, C. | 6 | 5 | 0.61 |