Gerard Margarit

On the Usage of GRECOSAR, an Orbital Polarimetric SAR Simulator of Complex Targets, to Vessel Classification Studies

This paper presents a synthetic aperture radar (SAR) simulator that is able to generate polarimetric SAR (POLSAR) and polarimetric inverse SAR data of complex targets. It solves the electromagnetic problem via high-frequency approximations, such as physical optics and the physical theory of diffraction, with notable computational efficiency. In principle, any orbital monostatic sensor working at any band, resolution, and operating mode can be modeled. To make simulations more realistic, the targets bearing and speed are considered, and for the particular case of vessels, even the translational and rotational movements induced by the sea state. All these capabilities make the simulator a powerful tool for supplying large amounts of data with precise scenario information and for testing future sensor configurations. In this paper, the usefulness of the simulator on vessel classification studies is assessed. Several simulated polarimetric images are presented to analyze the potentialities of coherent target decompositions for classifying complex geometries, thus basing an operational algorithm. The limitations highlighted by the results suggest that other approaches, like POLSAR interferometry, should be explored

Single-Pass Polarimetric SAR Interferometry for Vessel Classification

This paper presents a novel method for vessel classification based on single-pass polarimetric synthetic aperture radar (SAR) interferometry. It has been developed according to recent ship scattering studies that show that the polarimetric response of many types of vessels can be described by trihedral- and dihedral-like mechanisms. The adopted methodology is quite simple. The input interferometric data are decomposed in terms of the Pauli basis, and hence, one height image is derived for each simple mechanism. Then, the local maxima of these images are isolated, and a 3-D map of scatters is generated. The correlation of this map with the scattering distribution expected for a set of reference ships provides the final classification decision. The performance of the proposed method has been tested with the orbital SAR simulator developed at Universitat Politecnica de Catalunya. Different vessel models have been processed with a sensor configuration similar to the incoming TanDEM-X system. The analysis of diverse vessel bearings, vessel speeds, and sea states shows that the map of scatters matches reasonably the geometry of ships allowing a correct identification even for adverse environmental conditions.

Ship Classification in Single-Pol SAR Images Based on Fuzzy Logic

This paper presents a new ship classification methodology that uses single-pol synthetic aperture radar (SAR) images to categorize targets based on a fuzzy logic (FL) decision rule. As such, the method tries to overcome the lack of an operational solution that is able to reliably classify ships with one SAR channel. The method has the following three main stages: (1) radar signature isolation; (2) parametric vector (P) estimation; and (3) decision rule. The first part analyzes the reflectivity histogram of the ship signature to iteratively cluster the pixels of interest. Then, P is calculated by estimating the values of some macroscale features such as length, breadth, and radar cross section profile along the ship signature. Finally, the decision rule is evaluated with FL so that the measured vector P is correlated with the vectors associated with a set of reference categories. These categories have been defined based on user feedback and have been characterized with accurate simulation studies. Specifically, the values of P for each reference ship have been derived with the SAR simulator GRECOSAR. The classification method has been tested with several ENVISAT images acquired for the surroundings of the Strait of Gibraltar. Ground truth has been retrieved via transponder polls, which reveals a preliminary ratio of positive classifications close to 70%. Although this value is not definitive and more tests are needed, it is a good starting point.

Exploitation of Ship Scattering in Polarimetric SAR for an Improved Classification Under High Clutter Conditions

This paper evaluates the potentialities of polarimetric ship scattering for basing classification methods that provide reasonable performance within cluttered scenes. Both simulated and airborne polarimetric synthetic aperture radar (SAR) images have been used to validate the conclusions of a previous phenomenological study. Numerical simulations have been carried out with GRECOSAR, a polarimetric interferometric SAR simulation tool that is able to process highly complex targets with a fast and accurate radar-cross-section prediction module. A representative set of scenarios has been defined, which includes various realistic ship models, sea states, and imaging geometries. In all of them, a two-scale sea surface model precisely accounting for sea-ship interaction and sea clutter has been added. The analysis of different images has shown that, with an adequate spatial resolution, ships may be characterized by a particular spatial arrangement and polarization state distribution of dominant scattering centers. This feature has allowed one to propose a new classification algorithm, which shows a promising behavior after various preliminary tests. In this paper, the performance of this technique is further evaluated with realistic clutter. The results show that robust classification is possible even in highly cluttered scenes if quad-pol imagery is available. On the contrary, in low clutter conditions, the usage of less restrictive solutions, like circular dual-pol schemes, is feasible and may still get an acceptable performance.

Operational Ship Monitoring System Based on Synthetic Aperture Radar Processing

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.

Phenomenological Vessel Scattering Study Based on Simulated Inverse SAR Imagery

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.

Polarimetric Characterization and Temporal Stability Analysis of Urban Target Scattering

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 simulators 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 quasi-deterministic scattering behavior, nonprobabilistic models based on targets 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.

Grecosar, a SAR simulator for complex targets: Application to urban environments.

This paper presents a preliminary study about the scattering properties of urban-like scatters based on simulated SAR images. A simple target performed by a box of gypsum located over a perfectly conducting flat plane is analyzed for different views in both ISAR and SAR fully-polarimetric modes. The results are analyzed with the Pauli decomposition theorem and they show that the scattering response of such a target is dominated by a strong scatter, which polarimetric behavior depends on the relative orientation of the target with respect to the radar. Tests with interferometry shows that the height of the box can be reasonably retrieved despite of model simplicity.

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

The modeling of complex target response in SAR imagery is the main subject of this paper. The analysis of a large database of SAR images with polarimetric and interferometric capabilities is used to accurately establish how the different structural parts of targets interact with the incident signal. This allows to relate the reflectivity information provided by SAR images with specific geometries and to fix variation reflectivity patterns in terms of different imaging parameters such as image resolution, incidence angle, or operating frequency. Most of the used images have been obtained from the SAR simulator of complex targets developed at UPC, which is able to generate realistic data for a wide range of observation and environmental conditions. The result is a precise scattering-based SAR model that opens the door, among others, to an alternative way for reliable geometry retrieval. Under this approach, a novel SAR classification method for ships has been proposed. The preliminary evaluation in simulated scenarios shows a notable classification capability even under strong clutter and ship motion conditions. Due to these promising results, the same methodology is intended to be applied to urban areas. Concerns about possible model limitations and required improvements are preliminarily treated.

Analysis of the limitations of coherent polarimetric decompositions on vessel classification using simulated images

This paper presents a study performed with high resolution simulated SAR data that outline the limitations of polarimetric coherent decompositions on vessel classification. In these days, these theorems have been set up as the most advisable alternative for this application but an evident lack of real data avoids know their true usefulness. In this way, this study overcomes this limitation opening the doors to other alternatives, which would provide better performances in this research line.