Robust CFAR Detector Based on Truncated Statistics for Polarimetric Synthetic Aperture Radar

Constant false alarm rate (CFAR) algorithms using a local training window are widely used for ship detection with synthetic aperture radar (SAR) imagery. However, when the density of the targets is high, such as in busy shipping lines and crowded harbors, the background statistics may be contaminated by the presence of nearby targets in the training window. Recently, a robust CFAR detector based on truncated statistics (TS) was proposed. However, the truncation of data in the format of polarimetric covariance matrices is much more complicated with respect to the truncation of intensity (single polarization) data. In this article, a polarimetric whitening filter TS CFAR (PWF-TS-CFAR) is proposed to estimate the background parameters accurately in the contaminated sea clutter for PolSAR imagery. The CFAR detector uses a polarimetric whitening filter (PWF) to turn the multidimensional problem to a 1-D case. It uses truncation to exclude possible statistically interfering outliers and uses TS to model the remaining background samples. The algorithm does not require prior knowledge of the interfering targets, and it is performed iteratively and adaptively to derive better estimates of the polarimetric covariance matrix (although this is computationally expensive). The PWF-TS-CFAR detector provides accurate background clutter modeling, a stable false alarm property, and improves the detection performance in high-target-density situations. RadarSat2 data are used to verify our derivations, and the results are in line with the theory

Polarimetric SAR Speckle Noise Model

Synthetic aperture radar (SAR) data are affected by speckle noise, originated by the SAR system's coherent nature. The problem of speckle noise in one-dimensional (1-D) data is already solved, as speckle has a multiplicative characteristic. SAR polarimetry represents an extension to multidimensional data by the use of polarization wave diversity. As a consequence of the existence of a correlation degree between the SAR images, the 1-D speckle noise model cannot be extended to multidimensional SAR data. This paper is devoted to present a completely new speckle noise model for the complex covariance matrix describing polarimetric SAR data in the distributed scatterers case. As is shown, this new model is able to identify which are the noise mechanisms in all the covariance matrix elements. The speckle noise model is validated by using real L-band polarimetric data acquired with the German E-SAR sensor.Synthetic aperture radar (SAR) data are affected by speckle noise, originated by the SAR system’s coherent nature. The problem of speckle noise in one-dimensional (1-D) data is already solved, as speckle has a multiplicative characteristic. SAR polarimetry represents an extension to multidimensional data by the use of polarization wave diversity. As a consequence of the existence of a correlation degree between the SAR images, the 1-D speckle noise model cannot be extended to multidimensional SAR data. This paper is devoted to present a completely new speckle noise model for the complex covariance matrix describing polarimetric SAR data in the distributed scatterers case. As will be shown, this new model is able to identify which are the noise mechanisms in all the covariance matrix elements. The speckle noise model is validated by using real L-band polarimetric data acquired with the German E-SAR sensor

PolSAR Ship Detection Based on Neighborhood Polarimetric Covariance Matrix

The detection of small ships in polarimetric synthetic aperture radar (PolSAR) images is still a topic for further investigation. Recently, patch detection techniques, such as superpixel-level detection, have stimulated wide interest because they can use the information contained in similarities among neighboring pixels. In this article, we propose a novel neighborhood polarimetric covariance matrix (NPCM) to detect the small ships in PolSAR images, leading to a significant improvement in the separability between ship targets and sea clutter. The NPCM utilizes the spatial correlation between neighborhood pixels and maps the representation for a given pixel into a high-dimensional covariance matrix by embedding spatial and polarization information. Using the NPCM formalism, we apply a standard whitening filter, similar to the polarimetric whitening filter (PWF). We show how the inclusion of neighborhood information improves the performance compared with the traditional polarimetric covariance matrix. However, this is at the expense of a higher computation cost. The theory is validated via the simulated and measured data under different sea states and using different radar platforms

On the extension of multidimensional speckle noise model from single-look to multilook SAR imagery

Speckle noise represents one of the major problems when synthetic aperture radar (SAR) data are considered. Despite the fact that speckle is caused by the scattering process itself, it must be considered as a noise source due to the complexity of the scattering process. The presence of speckle makes data interpretation difficult, but it also affects the quantitative retrieval of physical parameters. In the case of one-dimensional SAR systems, speckle is completely determined by a multiplicative noise component. Nevertheless, for multidimensional SAR systems, speckle results from the combination of multiplicative and additive noise components. This model has been first developed for single-look data. The objective of this paper is to extend the single-look data model to define a multilook multidimensional speckle noise model. The asymptotic analysis of this extension, for a large number of averaged samples, is also considered to assess the model properties. Details and validation of the multilook multidimensional speckle noise model are provided both theoretically and by means of experimental SAR data acquired by the experimental synthetic aperture radar system, operated by the German Aerospace Center.Peer Reviewe

CFAR Ship Detection in Polarimetric Synthetic Aperture Radar Images Based on Whitening Filter

Polarimetric whitening filter (PWF) can be used to filter polarimetric synthetic aperture radar (PolSAR) images to improve the contrast between ships and sea clutter background. For this reason, the output of the filter can be used to detect ships. This paper deals with the setting of the threshold over PolSAR images filtered by the PWF. Two parameter-constant false alarm rate (2P-CFAR) is a common detection method used on whitened polarimetric images. It assumes that the probability density function (PDF) of the filtered image intensity is characterized by a log-normal distribution. However, this assumption does not always hold. In this paper, we propose a systemic analytical framework for CFAR algorithms based on PWF or multi-look PWF (MPWF). The framework covers the entire log-cumulants space in terms of the textural distributions in the product model, including the constant, gamma, inverse gamma, Fisher, beta, inverse beta, and generalized gamma distributions (GΓDs). We derive the analytical forms of the PDF for each of the textural distributions and the probability of false alarm (PFA). Finally, the threshold is derived by fixing the false alarm rate (FAR). Experimental results using both the simulated and real data demonstrate that the derived expressions and CFAR algorithms are valid and robust

Analyse des signaux radars polarimétriques en bandes C et L pour le suivi de l'humidité du sol de sites forestiers

Résumé : Dans les couverts forestiers, le suivi de l’humidité du sol permet de prévenir plusieurs désastres tels que la paludification, les incendies et les inondations. Comme ce paramètre est très dynamique dans l’espace et dans le temps, son estimation à grande échelle présente un grand défi, d’où le recours à la télédétection radar. Le capteur radar à synthèse d’ouverture (RSO) est couramment utilisé grâce à sa vaste couverture et sa résolution spatiale élevée. Contrairement aux sols nus et aux zones agricoles, le suivi de l’humidité du sol en zone forestière est très peu étudié à cause de la complexité des processus de diffusion dans ce type de milieu. En effet, la forte atténuation de la contribution du sol par la végétation et la forte contribution de volume issue de la végétation réduisent énormément la sensibilité du signal radar à l’humidité du sol. Des études portées sur des couverts forestiers ont montré que le signal radar en bande C provient principalement de la couche supérieure et sature vite avec la densité de la végétation. Cependant, très peu d’études ont exploré le potentiel des paramètres polarimétriques, dérivés d’un capteur polarimétrique comme RADARSAT-2, pour suivre l’humidité du sol sur les couverts forestiers. L’effet du couvert végétal est moins important avec la bande L en raison de son importante profondeur de pénétration qui permet de mieux informer sur l’humidité du sol. L’objectif principal de ce projet est de suivre l’humidité du sol à partir de données radar entièrement polarimétriques en bandes C et L sur des sites forestiers. Les données utilisées sont celles de la campagne terrain Soil Moisture Active Passive Validation EXperiment 2012 (SMAPVEX12) tenue du 6 juin au 17 juillet 2012 au Manitoba (Canada). Quatre sites forestiers de feuillus ont été échantillonnés. L’espèce majoritaire présente est le peuplier faux-tremble. Les données utilisées incluent des mesures de l’humidité du sol, de la rugosité de surface du sol, des caractéristiques des sites forestiers (arbres, sous-bois, litières…) et des données radar entièrement polarimétriques aéroportées et satellitaires acquises respectivement, en bande L (UAVSAR) à 30˚ et 40˚ et en bande C (RADARSAT-2) entre 20˚ et 30˚. Plusieurs paramètres polarimétriques ont été dérivés des données UAVSAR et RADARSAT-2 : les coefficients de corrélation (ρHHVV, φHHVV, etc); la hauteur du socle; l’entropie (H), l’anisotropie (A) et l’angle alpha extraits de la décomposition de Cloude-Pottier; les puissances de diffusion de surface (Ps), de double bond (Pd) extraites de la décomposition de Freeman-Durden, etc. Des relations entre les données radar (coefficients de rétrodiffusion multifréquences et multipolarisations (linéaires et circulaires) et les paramètres polarimétriques) et l’humidité du sol ont été développées et analysées. Les résultats ont montré que 1) En bande L, plusieurs paramètres optimaux permettent le suivi de l’humidité du sol en zone forestière avec un coefficient de corrélation significatif (p-value < 0,05): σ[indice supérieur 0] linéaire et σ[indice supérieur 0] circulaire (le coefficient de corrélation, r, varie entre 0,60 et 0,96), Ps (r entre 0,59 et 0,84), Pd (r entre 0,6 et 0,82), ρHHHV_30˚, ρVVHV_30˚, φHHHV_30˚ and φHHVV_30˚ (r entre 0,56 et 0,81) alors qu’en bande C, ils sont réduits à φHHHV, φVVHV et φHHVV (r est autour de 0,90). 2) En bande L, les paramètres polarimétriques n’ont pas montré de valeur ajoutée par rapport aux signaux conventionnels multipolarisés d’amplitude, pour le suivi de l’humidité du sol sur les sites forestiers. En revanche, en bande C, certains paramètres polarimétriques ont montré de meilleures relations significatives avec l’humidité du sol que les signaux conventionnels multipolarisés d’amplitude.Abstract : Over forest canopies, soil moisture monitoring allows to prevent many disasters such as paludification, fires and floods. As this parameter is very dynamic in space and time, its large-scale estimation is a great challenge, hence the use of radar remote sensing. Synthetic aperture radar (SAR) sensor is commonly used due to its wide spatial coverage and its high spatial resolution. Unlike bare soils and agricultural areas, only few investigations focused on the monitoring of soil moisture over forested areas due to the complexity of the scattering processes in this kind of medium. Indeed, the high attenuation of soil contribution by the vegetation and the high vegetation volume contribution significantly reduce the sensitivity of the radar signal to soil moisture. Studies conducted at C-band have shown that the radar signal mainly comes from the upper layer and it quickly saturates with the vegetation density. However, very few studies have explored the potential of polarimetric parameters derived from a fully polarimetric sensor such as RADARSAT-2, to monitor soil moisture over forest canopies. With its large penetration’s depth, vegetation cover effect is less important at L-band, allowing thus to better inform on soil moisture. The main objective of this project is to monitor soil moisture from fully polarime tric L and C bands radar data acquired over forested sites. The data used were collected during the field campaign of Soil Moisture Active Passive Validation EXperiment 2012 (SMAPVEX12) which took place from June 6 to July 17, 2012 in Manitoba (Canada). Four deciduous forested sites were sampled. The main species is the trembling aspen. The data used included measurements of soil moisture, soil surface roughness, characteristics of the forested sites (trees, undergrowth, litter, etc.) and fully polarimetric airborne and satellite radar data respectively acquired at L-band (UAVSAR) with 30 ̊ and at 40 ̊ incidence angles and at C-band (RADARSAT -2) between 20 ̊ and 30 ̊. Several polarimetric parameters were derived from UAVSAR and RADARSAT-2 data: the correlation c oefficients (ρHHVV, φHHVV, etc); the pedestal height; entropy (H), anisotropy (A) and alpha angle extracted from Cloude-Pottier decomposition; surface (Ps) and double bounce (Pd) scattering powers extracted from Freeman-Durden decomposition, etc. Relationships between radar backscattering data (multifrequency and multipolarisation (linear/circular) backscattering coefficients and polarimetric parameters) and soil moisture were developed and analyzed. The results showed that 1) at L-band, several optimal parameters allow soil moisture monitoring over forested sites with a significant correlation coefficient (p-value < 0.05): linear and circular σ[superscript 0] (the correlation coefficient, r, varies between 0.60 and 0.96), Ps (r varies between 0.59 and 0.84), Pd (r varies between 0.60 and 0.82), ρHHHV_30 ̊, ρVVHV_30 ̊, φHHHV_30 ̊ and φHHVV_30 ̊ (r varies between 0.56 and 0.81). However, at C-band, there are only few optimal parameters φHHHV, φVVHV and φHHVV (r is around 0.90) . 2) at L-band, polarimetric parameters did not show any added values for soil moisture monitoring over forested sites compared to multipolarised σ[superscript 0]. Nevertheless, at C-band some polarimetric parameters show better significant relationships with the soil moisture than the conventional multipolarised backscattering amplitudes

Estudio comparativo de filtros para el tratamiento de imágenes SAR

Aunque la tecnología de captura de imágenes satelitales avanza, el ruido como fenómeno físico siempre es una limitante para analizar adecuadamente las imágenes capturadas. En nuestro caso el ruido Speckle, cuyo estudio y análisis se viene realizando durante 20 años en el mundo, ha motivado investigaciones para reducirlo sin perder información en ese proceso. Nuestro trabajo muestra una variedad de procesos de filtraje más relevantes en el análisis de imágenes satelitales SAR y los comparamos con el fin de determinar el más adecuado. Este análisis es particularmente importante en nuestro país debido a que los estudios en el tema son bastante recientes y la geografía de Colombia muy variada. El Primer Capítulo abarca los preliminares del proyecto. El Segundo Capítulo es una introducción teórica a la Teledetección: todo lo referente al Radar de Apertura Sintética y los fenómenos físicos que se presentan cuando interactúan las microondas con el ambiente y con algunos terrenos en concreto. También se muestra lo relacionado a la teoría de imágenes, su proceso de digitalización desde su formación matemática. Por último se presenta los filtros y criterios de calidad a experimentar explicando su sentido estadístico. El Tercer Capítulo muestra los estudios comparativos que ya se han desarrollado y que han servido de justificación para realizar nuestro proyecto de investigación. Por último, en un Cuarto Capítulo, se encuentra la metodología de la investigación partiendo de la herramienta suministrada y comprobada en otros trabajos de procesamiento de imágenes y material obtenido del Instituto de Hidrología, Meteorología y Estudios Ambientales (IDEAM) sobre el municipio del Repelón en el departamento del Atlántico – Colombia y sobre la Ciudad de Cartagena.RESUMEN CONTENIDO 1 PLANTEAMIENTO DEL PROBLEMA 1.1 Contexto 1.2 Definición del problema 1.3 Formulación del problema 1.4 Justificación 1.5 Delimitación 1.6 Objetivo general 2 INTRODUCCIÓN A LA TELEDETECCIÓN 2.1 El Radar SAR y el Espectro Electromagnético 2.2 Radar de Apertura Sintética (SAR) 2.3 Las Microondas con el Ambiente 2.4 Espectro de los materiales en la superficie terrestre 2.5 Las microondas con la atmosfera y el suelo 2.6 Teoría de imágenes 2.7 Filtros 2.8 Medidas de calidad 3 ESTADO DEL ARTE 4 METODOLOGÍA DE LA INVESTIGACIÓN 4.1 Experimento 1: Análisis Estadístico imágenes sintéticas 4.2 Experimento 2: Comparación de imágenes filtradas imagen del Municipio del Repelón polarización HV con zoom 4.3 Experimento 3: Comparación estadística de filtros imagen de Cartagena con polarización HH 4.4 CONCLUSIONES 4.5 TRABAJOS FUTUROS BIBLIOGRAFÍA Anexo 1: Código Criterios de comparación GUI MatLabPregradoIngeniero en ElectrónicaIngeniería Electrónic