Scattering‐Based Model of the SAR Signatures of  Complex Targets for Classification Applications

Margarit, G.; Mallorquí, Jordi J.

doi:10.1155/2008/426267

Cited by 12 publications

(14 citation statements)

References 31 publications

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“…They are expected to be improved with the exploitation of the new generation of SAR sensors, as TerraSAR-X, CosmoSkymed or Radarsat-2. Their features permit the detection of small and less reflective ships and tackling automatic ship classification following the seed of recent works [9,10].…”

Section: Discussionmentioning

confidence: 99%

Operational Ship Monitoring System Based on Synthetic Aperture Radar Processing

2009

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This paper presents a Ship Monitoring System (SIMONS) working with Synthetic Aperture Radar (SAR) images. It is able to infer ship detection and classification information, and merge the results with other input channels, such as polls from the Automatic Identification System (AIS). Two main stages can be identified, namely: SAR processing and data dissemination. The former has three independent modules, which are related to Coastline Detection (CD), Ship Detection (SD) and Ship Classification (SC). The later is solved via an advanced web interface, which is compliant with the OpenSource standards fixed by the Open Geospatial Consortium (OGC). SIMONS has been designed to be a modular, unsupervised and reliable system that meets Near-Real Time (NRT) delivery requirements. From data ingestion to product delivery, the processing chain is fully automatic accepting ERS and ENVISAT formats. SIMONS has been developed by GMV Aerospace, S.A. with three main goals, namely: 1) To limit the dependence on the ancillary information provided by systems such as AIS.2) To achieve the maximum level of automatism and restrict human manipulation.3) To limit the error sources and their propagation. Spanish authorities have validated SIMONS. The results have been satisfactory and have confirmed that the system is useful for improving decision making. For single-polarimetric images with a resolution of 30 m, SIMONS permits the location of ships larger than 40 m with a classification ratio around 50% of positive matches. These values are expected to be improved with SAR data from new sensors. In the paper, the performance of SD and SC modules is assessed by cross-check of SAR data with AIS reports.

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Section: Discussionmentioning

confidence: 99%

Operational Ship Monitoring System Based on Synthetic Aperture Radar Processing

2009

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“…This results on realistic SAR images for most of the operating modes [10], [11], [14]. The realism of such images have allowed significant progress in different research fields, for instance, ship classification where a new Vessel Classification Algorithm has been proposed [15], [16].…”

Section: A Em Kernel: Grecomentioning

confidence: 98%

Polarimetric Characterization and Temporal Stability Analysis of Urban Target Scattering

Margarit

Mallorquí

Pipia

2010

IEEE Trans. Geosci. Remote Sensing

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Abstract-This paper studies the polarimetric-dispersion properties of urban targets and their evolution along time in terms of the geometrical configuration. The relations between target geometry and the scattering behavior have been defined through the analysis of large stacks of simulated images. Scattering maps and synthetic aperture radar (SAR) images have been synthesized with the numerical tool GRaphical Electromagnetic COmputing SAR for different qualitative models of two real buildings. Ground-based SAR (GB-SAR) data acquired in a subsidence measurement campaign has been used to assess the simulator's realism. These data have permitted the identification of the critical simulation parameters and their range of recommended values for realistic simulations. In the context of very high resolution images, the results derived from this study may be crucial for making progress in urban-image postprocessing. As the different resolution cells comprise few scattering centers showing a quasideterministic scattering behavior, nonprobabilistic models based on target's geometry seem more suited for scattering modeling. In these models, the geometry-scattering (GS) links precisely inferred from simulated images can be very important. In addition to change detection and land classification, GS models may help in improving the interpretation of subsidence results with differential interferometry. Certainly, new processing algorithms can be developed exploiting the available scattering data with more physical sense. In addition, they can take more advantage of the fine resolution and polarimetric capabilities of the new sensors, like TerraSAR-X or RADARSAT-2.

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“…For maritime environments, ship bearing, motions and velocity are managed with a surrounding sea surface, which is updated by a user-defined dynamic pattern [8]. Due to GRECO ® restrictions, the sea is modeled with small facets* taking the dielectric properties of salt water into account.…”

Section: Grecosarmentioning

confidence: 99%

“…Their analysis with Coherent Target Decompositions (CTD) [5, 6] have revealed certain dispersion stability along the radar aspect angle. The cause is the presence of Permanent Polarimetric Scatterers (PePS) that have a high Radar Cross Section (RCS) and a well-defined scattering pattern, which remains constant within a large solid angle [7, 8]. The spatial and polarimetric distribution of PePS has appeared to be particular for each vessel model, characterizing its macro-scale features.…”

Section: Introductionmentioning

confidence: 99%

Assessment of Polarimetric SAR Interferometry for Improving Ship Classification based on Simulated Data

Margarit

Mallorquí²

2008

Sensors

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This paper uses a complete and realistic SAR simulation processing chain, GRECOSAR, to study the potentialities of Polarimetric SAR Interferometry (POLInSAR) in the development of new classification methods for ships. Its high processing efficiency and scenario flexibility have allowed to develop exhaustive scattering studies. The results have revealed, first, vessels' geometries can be described by specific combinations of Permanent Polarimetric Scatterers (PePS) and, second, each type of vessel could be characterized by a particular spatial and polarimetric distribution of PePS. Such properties have been recently exploited to propose a new Vessel Classification Algorithm (VCA) working with POLInSAR data, which, according to several simulation tests, may provide promising performance in real scenarios. Along the paper, explanation of the main steps summarizing the whole research activity carried out with ships and GRECOSAR are provided as well as examples of the main results and VCA validation tests. Special attention will be devoted to the new improvements achieved, which are related to simulations processing a new and highly realistic sea surface model. The paper will show that, for POLInSAR data with fine resolution, VCA can help to classify ships with notable robustness under diverse and adverse observation conditions.

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Scattering‐Based Model of the SAR Signatures of Complex Targets for Classification Applications

Cited by 12 publications

References 31 publications

Operational Ship Monitoring System Based on Synthetic Aperture Radar Processing

Operational Ship Monitoring System Based on Synthetic Aperture Radar Processing

Polarimetric Characterization and Temporal Stability Analysis of Urban Target Scattering

Assessment of Polarimetric SAR Interferometry for Improving Ship Classification based on Simulated Data

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