Multiple reflections and improvement of edge scattering in GRECO RCS prediction code

GRECO code for monostatic RCS prediction in real time has been extended by considering multiple reflections between surfaces and improving the edge diffraction coefficients. Multiple reflections are analysed through a very efficient ray-tracing algorithm based on the graphical processing technique. Method of equivalent currents for edge scattering has been improved by Mitzner's and Michaeli's incremental length diffraction coefficients (ILDC). This communication presents the general features of GRECO code, in particular the advantages of the new graphical processing technique. Emphasis will be placed in the new features of GRECO still unpublished: the ray-tracing algorithm and the implementation of incremental length diffraction coefficients. Multiple reflections and improvement of edge scattering in GRECO RCS prediction code. Available from: https://www.researchgate.net/publication/238507602_Multiple_reflections_and_improvement_of_edge_scattering_in_GRECO_RCS_prediction_code [accessed May 31, 2017].Peer ReviewedPostprint (published version

Probabilistic inference method to discriminate closed water from sea ice using SENTINEL-1 Sar signatures

Consistent sea ice monitoring requires accurate estimates of sea ice concentration. Current retrieval algorithms are based on low-resolution microwave radiometry data with limited penetration depth and are unable to resolve surface characteristics of sea ice in sufficient detail which is necessary to discriminate intact sea ice from closed water. Important information about surface roughness conditions are contained in the distribution of radar backscattering images which can be - in principle - used to detect melt ponds and different sea ice types. In this work, a two-step probabilistic approach based on Expectation-Maximization and Bayesian inference considers the spatial and statistical characteristics of medium-resolution daily-available Sentinel-1 SAR images. The presented method segments sea ice into a number of separable classes and enables to discriminate surface water from the remaining sea ice types.The lead author was supported by “la Caixa” Foundation (ID 100010434) with the fellowship code LCF/BQ/D118/11660050, and received funding from the European Union's Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No. 713673. The project was also funded through the award “Unidad de Excelencia María de Maeztu” MDM-2016-0600, by the Spanish Ministry of Science and Innovation through the project “L-band” ESP2017-89463-C3-2-R, and the project “Sensing with Pioneering Opportunistic Techniques (SPOT)” RTI2018-099008-B-C21/AEI/10.13039/501100011033.Peer ReviewedPostprint (published version

An evaluation of soil moisture downscaling techniques using L.Band Airbone observations

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Strong RFI impact mitigation in the synthetic aperture interferometric radiometer

© 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.Radio Frequency Interference (RFI) is one of the problems causing the performance degradation in passive microwave radiometry. Especially, Synthetic Aperture Interferometric Radiometer (SAIR) is quite vulnerable to strong RFI. The Soil Moisture Ocean Salinity (SMOS) brightness temperature images show serious contamination by the RFI. The RFI affection in SAIR images should be mitigated or filtered out to retrieve the geophysical parameters. This work presents a method to RFI mitigation/filtering for SAIRs. Different from the existing method processing the brightness temperature image directly, RFI filtering of the subspace of covariance matrix is introduced, and the results are shown. The proposed method shows decent results for strong RFI with efficiency compared to the existing methods. © 2018 IEEE.Peer ReviewedPostprint (published version

Fast algorithms for radar cross section computation of complex objects

Radar cross section (RCS) of complex targets can be obtained in real time using the hardware capabilities of a high performance graphic workstation. Target geometry is modelled by a computer-aided design package. First order contribution to RCS is computed under physical optics high-frequency approximation. Real time computation is achieved through graphical processing of an image obtained with local illumination modeling of the target. Multiple scattering contribution can be obtained using radiosity algorithm, a recently developed global illumination method.Peer ReviewedPostprint (published version

Bayesian unsupervised machine learning approach to segment arctic sea ice using SMOS data

Microwave radiometry at L-band is sensitive to sea ice thickness (SIT) up to ~ 60 cm. Current methods to infer SIT depend on ice-physical properties and data provided by the ESA’s Soil Moisture and Ocean Salinity (SMOS) mission. However, retrieval accuracy is limited due to seasonally and regionally variable surface conditions during the formation and melting of sea ice. In this work, Arctic sea ice is segmented using a Bayesian unsupervised learning algorithm aiming to recognize spatial patterns by harnessing multi-incidence angle brightness temperature observations. The approach considers both statistical characteristics and spatial correlations of the observations. The temporal stability and separability of classes are analyzed to distinguish ambiguous from well-determined regions. Model uncertainty is quantified from class membership probabilities using information entropy. The presented approach opens up a new scope to improve current SIT retrieval algorithms, and can be particularly beneficial to investigate merged satellite products.This project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No.713673. It was also funded through the award “Unidad de Excelencia María de Maeztu” MDM-2016-0600, by the Spanish Ministry of Science and Innovation through the project “L-band” ESP2017-89463-C3-2-R, and the project “Sensing with Pioneering Opportunistic Techniques (SPOT)” RTI2018-099008-B-C21/AEI/10.13039/501100011033.Peer ReviewedPostprint (published version

Surface moisture and temperature trends anticipate drought conditions linked to wildfire activity in the Iberian Peninsula

In this study, drought conditions involving risk of fires are detected applying SMOS-derived soil moisture data and land surface temperature models. Moisture-temperature (SM-LST) patterns studied between 2010 and 2014 were linked to main fire regimes in the Iberian Peninsula. Most wildfires burned in warm and dry soils, but the analysis of pre-fire conditions differed among seasons. Absolute values of SM-LST were useful to detect prone- to-fire conditions during summer and early autumn. Complementarily, SM-LST anomalies were related to droughts and high fire activity in October 2011 and February-March 2012. These episodes were coincident with abnormally anticyclonic atmospheric conditions. Results show that combined trends of new soil moisture space-borne data and temperature models could enhance fire risk assessment capabilities. This contribution should be helpful to face the expected increase of wildfire activity derived from climate change.Peer ReviewedPostprint (published version

Sección recta de blancos radar complejos en tiempo real: aproximación de óptica física

Peer ReviewedPostprint (published version

Optimum Redundant Array Configurations for Earth Observation Aperture Synthesis Microwave Radiometers

Two-dimensional aperture synthesis radiometry is the technology selected for ESA's SMOS mission to provide high resolution L-band radiometric imagery. The array topology is a Y-shaped structure. The position and number of redundant elements to minimise instrument degradation in case of element failure(s) are studied

High-Frequency RCS of Perfectly Conducting or Coated Complex Objects in Real Time

This paper present a new and original approach to compute high-freqency radar cross section (RCS) of complex radar targets in real time using a 3-D graphic workstation. The aircraft is modelled with I-DEAS solid modeling software using a parametric surface approach. High-frequency RCS is obtained through Physical Optics (PO), Method of Equivalent Currents (MEC), Physical Theory of Diffraction (PTD) and Impedance Boundary Condition (IBC). Multiple scattering between target surfaces is also considered.Peer ReviewedPostprint (published version