Modifying the Yamaguchi Four-Component Decomposition Scattering Powers Using a Stochastic Distance

Model-based decompositions have gained considerable attention after the initial work of Freeman and Durden. This decomposition which assumes the target to be reflection symmetric was later relaxed in the Yamaguchi et al. decomposition with the addition of the helix parameter. Since then many decomposition have been proposed where either the scattering model was modified to fit the data or the coherency matrix representing the second order statistics of the full polarimetric data is rotated to fit the scattering model. In this paper we propose to modify the Yamaguchi four-component decomposition (Y4O) scattering powers using the concept of statistical information theory for matrices. In order to achieve this modification we propose a method to estimate the polarization orientation angle (OA) from full-polarimetric SAR images using the Hellinger distance. In this method, the OA is estimated by maximizing the Hellinger distance between the un-rotated and the rotated $T_{33}$ and the $T_{22}$ components of the coherency matrix $\mathbf{[T]}$. Then, the powers of the Yamaguchi four-component model-based decomposition (Y4O) are modified using the maximum relative stochastic distance between the $T_{33}$ and the $T_{22}$ components of the coherency matrix at the estimated OA. The results show that the overall double-bounce powers over rotated urban areas have significantly improved with the reduction of volume powers. The percentage of pixels with negative powers have also decreased from the Y4O decomposition. The proposed method is both qualitatively and quantitatively compared with the results obtained from the Y4O and the Y4R decompositions for a Radarsat-2 C-band San-Francisco dataset and an UAVSAR L-band Hayward dataset.Comment: Accepted for publication in IEEE J-STARS (IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing

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

A Depolarization Ratio Anomaly Detector to identify icebergs in sea ice using dual-polarization SAR images

Icebergs represent hazards to maritime traffic and offshore operations. Satellite Synthetic Aperture Radar (SAR) is very valuable for the observation of polar regions and extensive work was already carried out on detection and tracking of large icebergs. However, the identification of small icebergs is still challenging especially when these are embedded in sea ice. In this work, a new detector is proposed based on incoherent dual-polarization SAR images. The algorithm considers the limited extension of small icebergs, which are supposed to have a stronger cross polarization and higher cross- over co-polarization ratio compared to the surrounding sea or sea ice background. The new detector is tested with two satellite systems. Firstly, RADARSAT-2 quad-polarimetric images are analyzed to evaluate the effects of high resolution data. Subsequently a more exhaustive analysis is carried out using dual-polarization ground detected Sentinel-1a Extra Wide swath images acquired over the time span of two months. The test areas are on the East Coast of Greenland, where several icebergs have been observed. A quantitative analysis and a comparison with a detector using only the cross polarization channel is carried out exploiting grounded icebergs as test targets. The proposed methodology improves the contrast between icebergs and sea ice clutter by up to 75 times. This returns an improved probability of detection

A review of the applications of SAR polarimetry and polarimetric interferometry - an ESA funded study

International audienc

CLEAN technique for polarimetric ISAR

Inverse synthetic aperture radar (ISAR) images are often used for classifying and recognising targets. To reduce the amount of data processed by the classifier, scattering centres are extracted from the ISAR image and used for classifying and recognising targets. This paper addresses the problem of estimating the position and the scattering vector of target scattering centres from polarimetric ISAR images. The proposed technique is obtained by extending the CLEAN technique, which was introduced in radar imaging for extracting scattering centres from single-polarisation ISAR images. The effectiveness of the proposed algorithm, namely, the Polarimetric CLEAN (Pol-CLEAN) is tested on simulated and real dataM. Martorella, A. Cacciamano, E. Giusti, F. Berizzi, B. Haywood, and B. Bate

Review of Polarimetric and ionospheric effects on Sar, Insar and Palsar systems: requirements and correction methods

Este estudio proporciona una actualización de las herramientas polarimétricas que se utilizan actualmente para la extracción óptima de la información a partir de imágenes de Radares de Apertura Sintética, SAR, de imágenes Interferométricas de SAR, InSAR e imágenes polarimétricas de SAR en la banda L, PALSAR. Los fundamentos de la teoría polarimétrica son discutidos en el contexto del radar de apertura sintética (SAR). Se revisa la calibración polarimétrica SAR, que es un tema importante para la extracción de información. Es considerada la extracción de información usando los parámetros de ondas dispersadas recibidas. Se proponen algunos esquemas de corrección ionosférica para las ondas transmitidas por el radar de apertura sintética (SAR) y para la interferometría SAR polarimétrica (PolInSAR) en el espacio. La variación temporal y espacial de la densidad de electrónica en la alta atmosfera afecta la propagación del pulso de radar dando lugar a distorsiones de la imagen. Se estima el Contenido Electrónico Total (CET) mediante la aplicación de la ecuación de Appleton-Hartree debido a distorsiones de enfoque, polarimetría e interferometría. Se propo-ne un estimador combinado que produce estimaciones diferenciales de CET. Se discute además el efecto de la estructura vertical de la ionosfera desde la fase interferométrica y se describen instrucciones importantes para la investigación futura.This study provides an update of the polarimetric tools currently used for optimal extraction of information from polarimetric SAR (Synthetic Aperture Radar), INSAR (Interferometric Synthetic Aperture Radar) and PALSAR (Phase Array L-band Synthetic Aperture Radar) imagery. The fundamentals of polarimetric theory are discussed in the context of synthetic aperture radar (SAR). Polarimetric SAR calibration, which is important for the extraction of subject information, is reviewed. Extraction of information using the received scattered wave is considered. Some schemes for ionospheric correction to synthetic aperture radar (SAR) and the wave interferometry (PolInSAR) are proposed. Temporal and spatial variations of the electronic density in the upper atmosphere affect radar pulse propagation and, thereby, result in distortion of the image. Due to distortions of focus, polarimetry and interferometry, the Total Electron Content (TEC) has been estimated by applying the Appleton-Hartree equation. We propose a combined estimator that reliably estimates of TEC differentials. We also discuss the effect of the vertical structure of the ionosphere from the interferometric phase and outline important avenues for future research.Fil: Rios, Victor Hugo. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de Tucuman. Facultad de Ciencias Exactas y Tecnologia. Departamento de Fisica; Argentin

Statistical tests for a ship detector based on the Polarimetric Notch Filter

Ship detection is an important topic in remote sensing and Synthetic Aperture Radar has a valuable contribution, allowing detection at night time and with almost any weather conditions. Additionally, polarimetry can play a significant role considering its capability to discriminate between different targets. Recently, a new ship detector exploiting polarimetric information was developed, namely the Geometrical Perturbation Polarimetric Notch Filter (GP-PNF). This work is focused on devising two statistical tests for the GP-PNF. The latter allow an automatic and adaptive selection of the detector threshold. Initially, the probability density function (pdf) of the detector is analytically derived. Finally, the Neyman-Pearson (NP) lemma is exploited to set the threshold calculating probabilities using the clutter pdf (i.e. a Constant False Alarm Rate, CFAR) and a likelihood ratio (LR). The goodness of fit of the clutter pdf is tested with four real SAR datasets acquired by the RADARSAT-2 and the TanDEM-X satellites. The former images are quad-polarimetric, while the latter are dual-polarimetric HH/VV. The data are accompanied by the Automatic Identification System (AIS) location of vessels, which facilitates the validation of the detection masks. It can be observed that the pdf's fit the data histograms and they pass the two sample Kolmogorov-Smirnov and χ2 tests