Study of sea clutter influence in ship classification algorithms based on Polarimetric SAR Inteferometry

This paper is focused to evaluate the influence of sea clutter in the performance of ship classification algorithms based on single-pass Polarimetric SAR Interferometry (PolInSAR). For such purpose, series of numerical simulations have been carried out with GRECOSAR, the SAR simulator of complex targets developed by UPC. There, different types of vessels have been considered for a TerraSAR-X like sensor and a sea surface following the two-scale wave approach. The quality of ship discrimination has been quantitatively evaluated with a novel identification method that exploits the particular scattering properties of ships. The results show that the presence of clutter does not notably drop identification performance, despite negative matches can be observed in some particular situations. But the requirement of single-pass interferometric capabilities is not achieved by any of the existing orbital system. This drawback can difficult the validation of what has been observed in simulation environments and can be one of the most limiting factors for the practical implementation of these techniques. Ideas and possible solutions to relax the system requirements are preliminary discussed.Postprint (published version

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 PolitÈcnica 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.Peer Reviewe

On the usage of GRECOSAR: an orbital polarimetric SAR simulator of complex targets for 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 target’s 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.Peer Reviewe

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 target’s 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.Peer Reviewe

Electromagnetic backscatter modelling of icebergs at c-band in an ocean environment

This thesis outlines the development of an electromagnetic (EM) backscatter model of icebergs. It is a necessary first step for the generation of in-house synthetic aperture radar (SAR) data of icebergs to support optimum iceberg/ship classifier design. The EM modelling was developed in three stages. At first, an EM backscatter model was developed to generate simulated SAR data chips of iceberg targets at small incidence angles. The model parameters were set to mimic a dual polarized dataset collected at C-Band with the Sentinel-1A satellite. The simulated SAR data chips were compared with signatures and radiometric properties of the satellite data, including total radar cross section (TRCS). A second EM model was developed to mimic the parameters of a second SAR data collection with RADARSAT-2; this second data collection was at larger incidence angles and was fully polarimetric (four channels and interchannel phase). The full polarimetric SAR data allowed for a comparison of modelled TRCS and polarimetric decompositions. Finally, the EM backscatter models were tested in the context of iceberg/ship classification by comparing the performance of various computer vision classifiers using both simulated and real SAR image data of iceberg and vessel targets. This step is critical to check the compatibility of simulated data with the real data, and the ability to mix real and simulated SAR imagery for the generation of skilled classifiers. An EM backscatter modelling tool called GRECOSAR was used for the modelling work. GRECOSAR includes the ability to generate small scenes of the ocean using Pierson-Moskowitz spectral parameters. It also allows the placement of a 3D target shape into that ocean scene. Therefore, GRECOSAR is very useful for simulating SAR targets, however it can only model single layer scattering from the targets. This was found to be limiting in that EM scattering throughout volume of the iceberg could not be generated. This resulted in EM models that included only surface scattering of the iceberg. In order to generate realistic SAR scenes of icebergs on the ocean, 3D models of icebergs were captured in a series of field programs off the coast of Newfoundland and Labrador, Canada. The 3D models of the icebergs were obtained using a light detection and ranging (LiDAR) and multi-beam sonar data from a specially equipped vessel by a team of C-CORE. While profiling the iceberg targets, SAR images from satellites were captured for comparison with the simulated SAR images. The analysis of the real and simulated SAR imagery included comparisons of TRCS, SAR signature morphology and polarimetric decompositions of the targets. In general, these comparisons showed a good consistency between the simulated and real SAR scene. Simulations were also performed with varying target orientation and sea conditions (i.e., wind speed and direction). A wide variability of the TRCS and SAR signature morphology was observed with varying scene parameters. Icebergs were modelled using a high dielectric constant to mimic melting iceberg surfaces as seen during field work. Given that GRECOSAR could only generate surface backscatter, a mathematical model was developed to quantify the effect of melt water on the amount of surface and volume backscatter that might be expected from the icebergs. It was found that the icebergs in a high state of melt should produce predominantly surface scatter, thus validating the use of GRECOSAR for icebergs in this condition. Once the simulated SAR targets were validated against the real SAR data collections, a large dataset of simulated SAR chips of ships and icebergs were created specifically for the purpose of target classification. SAR chips were generated at varying imaging parameters and target sizes and passed on to an iceberg/ship classifier. Real and simulated SAR chips were combined in varying quantities (or targets) resulting in a series of different classifiers of varying skill. A good agreement between the classifier’s performance was found. This indicates the compatibility of the simulated SAR imagery with this application and provides an indication that the simulated data set captures all the necessary physical properties of icebergs for ship and iceberg classification

Spaceborne synthetic aperture radar: Current status and future directions. A report to the Committee on Earth Sciences, Space Studies Board, National Research Council

This report provides a context in which questions put forth by NASA's Office of Mission to Planet Earth (OMPTE) regarding the next steps in spaceborne synthetic aperture radar (SAR) science and technology can be addressed. It summarizes the state-of-the-art in theory, experimental design, technology, data analysis, and utilization of SAR data for studies of the Earth, and describes potential new applications. The report is divided into five science chapters and a technology assessment. The chapters summarize the value of existing SAR data and currently planned SAR systems, and identify gaps in observational capabilities needing to be filled to address the scientific questions. Cases where SAR provides complementary data to other (non-SAR) measurement techniques are also described. The chapter on technology assessment outlines SAR technology development which is critical not only to NASA's providing societally relevant geophysical parameters but to maintaining competitiveness in SAR technology, and promoting economic development

Oil spill and ship detection using high resolution polarimetric X-band SAR data

Among illegal human activities, marine pollution and target detection are the key concern of Maritime Security and Safety. This thesis deals with oil spill and ship detection using high resolution X-band polarimetric SAR (PolSAR). Polarimetry aims at analysing the polarization state of a wave field, in order to obtain physical information from the observed object. In this dissertation PolSAR techniques are suggested as improvement of the current State-of-the-Art of SAR marine pollution and target detection, by examining in depth Near Real Time suitability

Classification of ocean vessels from low resolution satellite SAR images

In the long term it is beneficial to a country's economy to exploit the maritime environment surrounding it responsibly. It is also beneficial to protect this environment from poaching and pollution. To achieve this the responsible parties of a country must have an awareness of what is transpiring in the maritime domain. Synthetic aperture radar can provide an image, regardless of weather or light conditions, of the ocean showing most vessels therein. To monitor the ocean, using synthetic aperture radar imagery, at the lowest cost would require large swath synthetic aperture radar imagery. There exists a trade-off between large swath imagery and the image's resolution resulting in the largest swath image having the poorest resolution. Existing research has shown that it is possible to use coarse resolution synthetic aperture radar imagery to detect vessels at sea, but little work has been done on classifying those vessels. This research aims to investigate the coarse resolution classification information gap. This is done by using a dataset of matching synthetic aperture radar and ship transponder data to train a statistical classification algorithm in order to classify or estimate the length of vessels based on features extracted from their synthetic aperture radar image. The results of this research show that coarse resolution (approximately 40 m per pixel) synthetic aperture radar imagery is able to estimate vessel size for larger classes and provides insight on which vessel classes would require finer resolutions in order to be detected and classified reliably. The range of smaller vessel classes is usually limited to ports and fishing zones. These zones can be mapped using historical vessel transponder data and so a dedicated surveillance campaign can be optimised to use higher resolution products in these areas. The size estimation from the machine learning algorithm performs better than current techniques.Dissertation (MEng)--University of Pretoria, 2017.Electrical, Electronic and Computer EngineeringMEngUnrestricte

Ocean Remote Sensing with Synthetic Aperture Radar

The ocean covers approximately 71% of the Earth’s surface, 90% of the biosphere and contains 97% of Earth’s water. The Synthetic Aperture Radar (SAR) can image the ocean surface in all weather conditions and day or night. SAR remote sensing on ocean and coastal monitoring has become a research hotspot in geoscience and remote sensing. This book—Progress in SAR Oceanography—provides an update of the current state of the science on ocean remote sensing with SAR. Overall, the book presents a variety of marine applications, such as, oceanic surface and internal waves, wind, bathymetry, oil spill, coastline and intertidal zone classification, ship and other man-made objects’ detection, as well as remotely sensed data assimilation. The book is aimed at a wide audience, ranging from graduate students, university teachers and working scientists to policy makers and managers. Efforts have been made to highlight general principles as well as the state-of-the-art technologies in the field of SAR Oceanography

Electromagnetic modeling for SAR polarimetry and interferometry

Investigation of the globe remotely from hundreds of kilometers altitude, and fast growing of environmental and civil problems, triggered the necessity of development of new and more advanced techniques. Electromagnetic modeling of polarimetry and interferometry has always been a key driver in remote sensing research, ever since of the First pioneering sensors were launched. Polarimetric and interferometric SAR (Synthetic Aperture Radar) surveillance and mapping of the Earth surface has been attracting lots of interest since 1970s. This thesis covers two SAR's main techniques: (1) space-borne Interferometric Synthetic Aperture Radar (InSAR), which has been used to measure the Earth's surface deformation widely, and (2) SAR Polarimetry, which has been used to retrieve soil and vegetation physical parameters in wide areas. Time-series InSAR methodologies such as PSI (Permanent Scatterer Interferometry) are designed to estimate the temporal characteristics of the Earth's deformation rates from multiple InSAR images acquired over time. These techniques also enable us to overcome the limitations that conventional InSAR suffer, with a very high accuracy and precision. In this thesis, InSAR time-series analysis and modeling basis, as well as a case study in the Campania region (Italy), have been addressed. The Campania region is characterized by intense urbanization, active volcanoes, complicated fault systems, landslides, subsidence, and hydrological instability; therefore, the stability of public transportation structures is highly concerned. Here Differential Interferometric Synthetic Aperture Radar (DInSAR), and PSI techniques have been applied to a stack of 25 X-band radar images of Cosmo-SkyMed (CSK) satellites collected over an area in Campania (Italy), in order to monitor the railways' stability. The study area was already under investigation with older, low-resolution sensors like ERS1&2 and ENVISAT-ASAR before, but the number of obtained persistent scatterers (PSs) was too limited to get useful results. With regard to SAR polarimetry, in this thesis a fully polarimetirc SAR simulator has been presented, which is based on the use of sound direct electromagnetic models and it is able to provide as output the simulated raw data of all the three polarization channels in such a way as to obtain the correct covariance or coherence matrixes on the final focused polarimetic radar images. A fast Fourier-domain approach is used for the generation of raw signals. Presentation of theory is supplemented by meaningful experimental results, including a comparison of simulations with real polarimetric scattering data