Moving Target Analysis in ISAR Image Sequences with a Multiframe Marked Point Process Model

In this paper we propose a Multiframe Marked Point Process model of line segments and point groups for automatic target structure extraction and tracking in Inverse Synthetic Aperture Radar (ISAR) image sequences. For the purpose of dealing with scatterer scintillations and high speckle noise in the ISAR frames, we obtain the resulting target sequence by an iterative optimization process, which simultaneously considers the observed image data and various prior geometric interaction constraints between the target appearances in the consecutive frames. A detailed quantitative evaluation is performed on 8 real ISAR image sequences of different carrier ship and airplane targets, using a test database containing 545 manually annotated frames

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

Analysis of the Robustness of Bistatic Inverse Synthetic Aperture Radar in the Presence of Phase Synchronisation Errors

Bistatic inverse synthetic aperture radar (B-ISAR) has the potential to become the radar imaging tool for obtaining noncooperative target images in arbitrary bistatic configurations. A monostatic ISAR processor is used here to form B-ISAR images and its robustness is tested with respect to phase synchronisation errors and rapidly time-varying bistatic configurations. Specifically, the B-ISAR point spread function (PSF) is analytically derived and the problem of B-ISAR image autofocusing is reformulated in such conditions. It is shown that, in most bistatic scenarios, the range-Doppler (RD) based monostatic ISAR processor is able to form focussed B-ISAR images. Simulation results are used to support the theoretical results

A Novel Approach for ISAR Image Cross-Range Scaling

Inverse synthetic aperture radar (ISAR) imaging systems produce electromagnetic images of targets in the range-Doppler domain. In order to rescale the image in a homogeneous range-cross range domain (meters by meters), the modulus of the target effective rotation vector must be known. Although in some cases it can be retrieved by means of ancillary data, in most cases the modulus of the target effective rotation vector must be estimated. A blind technique is proposed for estimating the modulus of the target effective rotation vector that exploits information carried by the chirp rate of scattering centres. A technique based on image segmentation, local polynomial Fourier transform (LPFT), and image contrast (IC) maximisation is used in order to extract the scattering centres and estimate their chirp rate. Simulated and real data analyses are provided to confirm the effectiveness of the proposed algorithm

Optimal Sensor Positioning for Inverse Synthetic Aperture Radar

Noncooperative target recognition (NCTR) is often based on the use of inverse synthetic aperture radar (ISAR) images. Although ISAR systems are also able to provide an image of the target when the target's motions are not known a priori, the interpretation of the obtained image is not straightforward, and therefore, the target recognition becomes less effective. This is due to the fact that the image projection plane (IPP), which depends on both the radar position and the target's motions, cannot be predicted in typical ISAR scenarios. Given some target's motions the only degree of freedom with which to force the orientation of the IPP to be a desired one is the radar position. The criteria for defining the optimal ISAR sensor position are introduced. The theoretical basis for optimising the sensor position, given a desired IPP, is also provided. The effectiveness of the proposed method is then tested on real data