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

Estudio de un evento de quema de biomasa en la región Centro-Norte de Argentina en Agosto de 2018, mediante el uso de sensores satelitales y mediciones en supercie

Este trabajo tiene como objetivo analizar la deteccion de quema de biomasa en la region centro-norte delterritorio Argentino, que involucra principalmente a las provincias de Chaco, Formosa, Tucuman, Santiago delEstero, Santa Fe y Cordoba, entre el 27 y el 30 de agosto de 2018, utilizando mediciones satelitales y terrestres.Los aerosoles provenientes de la de quema de biomasa son los que mas afectan a America del Sur. Anualmente,desde mediados de agosto a principios de noviembre, se producen importantes quemas de pastizales que tienen suorigen en la zona centro-norte de Argentina, Bolivia, Paraguay y centro de Brasil, generalmente provocados por elhombre luego de la cosecha, para la eliminacion de desechos producto de la actividad agrcola y la deforestacion.Estas quemas producen importantes columnas de humo que pueden viajar cientos de kilometros transportadas porlos vientos desde su origen, afectando la calidad de aire de una gran extension territorial. Se analizan medicionessatelitales de los sensores MODIS (AQUA-TERRA) y TROPOMI (Sentinel-5p), de las cuales se estudian paraeste evento las siguientes variables: el ndice de absorcion de aerosoles (AI), el espesor optico de aerosoles (AOD)y la columna total de dioxido de nitrogeno y monoxido de carbono. Ademas se presentan las capturas satelitalesdel area afectada, representadas en RGB color verdadero. Tambien se calculan las retrotrayectorias con el modeloHYSPLIT/NOAA y la circulacion de viento de la base de datos NCEP/NCAR. Complementariamente se analizanlas mediciones del sistema LIDAR instalado en CITEDEF Villa Martelli, Buenos Aires, para determinar la alturade las capas de humo que llegan a la region. Ademas, se evaluan los datos de espesor optico de aerosoles delas estaciones de AERONET/NASA de Buenos Aires, Cordoba y Tucuman y se calcula, para dichas estaciones,el Coeciente declasicar los aerosoles.Angstrom, parametro sensible al radio medio de las partculas en suspension, lo que permite.Fil: García Ferreyra, M. F.. Comision Nacional de Actividades Espaciales; ArgentinaFil: Della Ceca, L.. Red Argentina de Municipios; ArgentinaFil: Casasola, F. I.. Ministerio de Defensa; ArgentinaFil: Martorella, Evangelina. Consejo Nacional de Investigaciones Científicas y Técnicas. Unidad de Investigación y Desarrollo Estratégico para la Defensa. Ministerio de Defensa. Unidad de Investigación y Desarrollo Estratégico para la Defensa; ArgentinaFil: Brusca, S.. Consejo Nacional de Investigaciones Científicas y Técnicas. Unidad de Investigación y Desarrollo Estratégico para la Defensa. Ministerio de Defensa. Unidad de Investigación y Desarrollo Estratégico para la Defensa; ArgentinaFil: D'elia, Raul Luis. Consejo Nacional de Investigaciones Científicas y Técnicas. Unidad de Investigación y Desarrollo Estratégico para la Defensa. Ministerio de Defensa. Unidad de Investigación y Desarrollo Estratégico para la Defensa; ArgentinaFil: Pereyra, C.. Servicio Geográfico Militar; ArgentinaFil: Pereyra, A.. Consejo Nacional de Investigaciones Científicas y Técnicas. Unidad de Investigación y Desarrollo Estratégico para la Defensa. Ministerio de Defensa. Unidad de Investigación y Desarrollo Estratégico para la Defensa; ArgentinaFil: Raponi, Marcelo Martín. Consejo Nacional de Investigaciones Científicas y Técnicas. Unidad de Investigación y Desarrollo Estratégico para la Defensa. Ministerio de Defensa. Unidad de Investigación y Desarrollo Estratégico para la Defensa; ArgentinaFil: Ristori, Pablo Roberto. Consejo Nacional de Investigaciones Científicas y Técnicas. Unidad de Investigación y Desarrollo Estratégico para la Defensa. Ministerio de Defensa. Unidad de Investigación y Desarrollo Estratégico para la Defensa; ArgentinaFil: Otero, Lidia Ana. Consejo Nacional de Investigaciones Científicas y Técnicas. Unidad de Investigación y Desarrollo Estratégico para la Defensa. Ministerio de Defensa. Unidad de Investigación y Desarrollo Estratégico para la Defensa; Argentina104 Reunión de la Asociación de Física ArgentinaSanta FeArgentinaAsociación de Física Argentin

the prevention of chronic diseases through ehealth a practical overview

Disease prevention is an umbrella term embracing individual-based or population-based interventions aimed at preventing the manifestation of diseases (primary prevention), reducing the impact of a disease that has arisen (secondary prevention), or mitigating the impact of an ongoing illness (tertiary prevention). Digital health has the potential to improve prevention of chronic diseases. Its application ranges from effective mHealth weight-loss intervention to prevent or delay the onset of diabetes in overweight adults to the cost-effective intervention on the provision of mental-health care via mobile-based or Internet-based programs to reduce the incidence or the severity of anxiety. The present contribution focuses on the effectiveness of eHealth preventive interventions and on the role of digital health in improving health promotion and disease prevention. We also give a practical overview on how eHealth interventions have been effectively implemented, developed, and delivered for the primary, secondary, and tertiary prevention of chronic diseases

ISAR image autofocus using 2D-polynomials

In this paper the authors propose a novel approach to ISAR image autofocus that is based on the use of two-dimensional polynomials derived from multivariable Taylor series expansions of the baseband signal. Such a novel approach follows a new interpretation of classical ISAR signal modeling and at the same time it provides the means for a deeper analysis and understanding of ISAR image formation using two-dimensional Fourier transforms. The theoretical findings, although to be considered at a preliminary stage, are supported by both simulations and real data analysis

ISAR image autofocus using 2D-polynomials

In this paper the authors propose a novel approach to ISAR image autofocus that is based on the use of two-dimensional polynomials derived from multivariable Taylor series expansions of the baseband signal. Such a novel approach follows a new interpretation of classical ISAR signal modeling and at the same time it provides the means for a deeper analysis and understanding of ISAR image formation using two-dimensional Fourier transforms. The theoretical findings, although to be considered at a preliminary stage, are supported by both simulations and real data analysis.</p

ISAR image autofocus using 2D-polynomials

In this paper the authors propose a novel approach to ISAR image autofocus that is based on the use of two-dimensional polynomials derived from multivariable Taylor series expansions of the baseband signal. Such a novel approach follows a new interpretation of classical ISAR signal modeling and at the same time it provides the means for a deeper analysis and understanding of ISAR image formation using two-dimensional Fourier transforms. The theoretical findings, although to be considered at a preliminary stage, are supported by both simulations and real data analysis.</p

Distributed radar multi target tracking based on range-Doppler measurements

In this article we present a method for multiple target tracking using multiple sensors with low azimuth resolution (-3dB beamwidth of about 60°). Due to the scarce azimuth resolution, the data association is performed using range and Doppler information only.</p

Polarimetrically Persistent Scatterer Based Automatic Target Recognition

Reliable automatic target recognition (ATR) systems based on inverse synthetic aperture radar (ISAR) images require a robust feature selection. An ATR system based on polarimetric ISAR images has been recently proposed that extracts bright scatterers and uses their polarimetric signatures to define classification features. Since bright scatterers could be the results of multiple scattering, the concept of polarimetrically persistent scatterers (PPSs) has been introduced in a recent work. PPS is usually associated with single scattering mechanism and, therefore, may prove to be more robust for classification purposes. In this paper, an ATR system is defined that makes use of PPS. Furthermore, a detailed analysis is carried out to emphasize the meaning of PPSs when used for ATR