Design and validation of a dual-band circular polarization patch antenna and stripline combiner for the FSSCat mission

The FMPL-2 payload on board the 3Cat-5/A 6 Unit CubeSat, part of the FSSCat CubeSat mission, includes a dual L-Band Microwave Radiometer and a Global Navigation Satellite System Reflectometer, in one instrument, implemented in a Software Defined Radio. One of the design challenges of this payload was its Nadir looking Antenna, which had to be directive (> 12 dB), dual-band at 1400–1427 MHz and 1575.42 MHz, left-hand circularly polarized, and with important envelope restrictions, notably with a low profile. After a trade-off analysis, the best design solution appeared to be an array of six elements each of them being a stacked dual-band patch antenna, with diagonal feed to create the circular polarization, and a six to one stripline combiner. The design process of the elementary antennas first includes a theoretical analysis, to obtain the approximate dimensions. Then, by means of numerical simulations, prototyping, and adjusting the results in the simulations, the manufacturing errors and dielectric constant tolerances, to which patch antennas are very sensitive, can be characterized. A similar approach is taken with the combiner. This article includes the theoretical analysis, simulations, and prototype results, including the Flight Model assembly and characterizationThis work was by the Programa Estatal para Impulsar la Investigación Científico-Técnica y su Transferencia, del Plan Estatal de Investigación Científica, Técnica y de Innovación 2021-2023 (Spain) and in part by the European Social Fund (ESF). It is also funded in part by the Secretaria d’Universitats i Recerca del Departament d’Empresa i Coneixement de la Generalitat de Catalunya 2017 SGR 376 and 2017 SGR 219. This work has also been founded by the grant PID2019-106808RA-I00 funded by MCIN/AEI/10.13039/501100011033. Finally, this research was possible thanks to the FI-2019 grant from AGAUR-Generalitat de Catalunya, Spain.Peer ReviewedPostprint (published version

Improved gnss-r altimetry methods: Theory and experimental demonstration using airborne dual frequency data from the microwave interferometric reflectometer (mir)

Altimetric performance of Global Navigation Satellite System - Reflectometry (GNSS-R) instruments depends on receiver’s bandwidth and signal-to-noise ratio (SNR). The altimetric delay is usually computed from the time difference between the peak of the direct signal waveform and the maximum of the derivative of the reflected signal waveform. Dual-frequency data gathered by the airborne Microwave Interferometric Reflectometer (MIR) in the Bass Strait, between Australia and Tasmania, suggest that this approach is only valid for flat surfaces and large bandwidth receivers. This work analyses different methods to compute the altimetric observables using GNSS-R. A proposed novel methodThis work was funded by the Spanish Ministry of Science, Innovation and Universities, “Sensing with Pioneering Opportunistic Techniques”, grant RTI2018-099008-B-C21/AEI/10.13039/ 501100011033, and the grant for recruitment of early-stage research staff FI-DGR 2015 of the AGAUR— Generalitat de Catalunya (FEDER), Spain, and the grant for recruitment of early-stage research staff FI 2018 of the AGAUR—Generalitat de Catalunya (FEDER), Spain, and Unidad de Excelencia María de Maeztu MDM-2016-060Postprint (published version

Treatment with tocilizumab or corticosteroids for COVID-19 patients with hyperinflammatory state: a multicentre cohort study (SAM-COVID-19)

Objectives: The objective of this study was to estimate the association between tocilizumab or corticosteroids and the risk of intubation or death in patients with coronavirus disease 19 (COVID-19) with a hyperinflammatory state according to clinical and laboratory parameters. Methods: A cohort study was performed in 60 Spanish hospitals including 778 patients with COVID-19 and clinical and laboratory data indicative of a hyperinflammatory state. Treatment was mainly with tocilizumab, an intermediate-high dose of corticosteroids (IHDC), a pulse dose of corticosteroids (PDC), combination therapy, or no treatment. Primary outcome was intubation or death; follow-up was 21 days. Propensity score-adjusted estimations using Cox regression (logistic regression if needed) were calculated. Propensity scores were used as confounders, matching variables and for the inverse probability of treatment weights (IPTWs). Results: In all, 88, 117, 78 and 151 patients treated with tocilizumab, IHDC, PDC, and combination therapy, respectively, were compared with 344 untreated patients. The primary endpoint occurred in 10 (11.4%), 27 (23.1%), 12 (15.4%), 40 (25.6%) and 69 (21.1%), respectively. The IPTW-based hazard ratios (odds ratio for combination therapy) for the primary endpoint were 0.32 (95%CI 0.22-0.47; p < 0.001) for tocilizumab, 0.82 (0.71-1.30; p 0.82) for IHDC, 0.61 (0.43-0.86; p 0.006) for PDC, and 1.17 (0.86-1.58; p 0.30) for combination therapy. Other applications of the propensity score provided similar results, but were not significant for PDC. Tocilizumab was also associated with lower hazard of death alone in IPTW analysis (0.07; 0.02-0.17; p < 0.001). Conclusions: Tocilizumab might be useful in COVID-19 patients with a hyperinflammatory state and should be prioritized for randomized trials in this situatio

Spatiotemporal Characteristics of the Largest HIV-1 CRF02_AG Outbreak in Spain: Evidence for Onward Transmissions

Background and Aim: The circulating recombinant form 02_AG (CRF02_AG) is the predominant clade among the human immunodeficiency virus type-1 (HIV-1) non-Bs with a prevalence of 5.97% (95% Confidence Interval-CI: 5.41–6.57%) across Spain. Our aim was to estimate the levels of regional clustering for CRF02_AG and the spatiotemporal characteristics of the largest CRF02_AG subepidemic in Spain.Methods: We studied 396 CRF02_AG sequences obtained from HIV-1 diagnosed patients during 2000–2014 from 10 autonomous communities of Spain. Phylogenetic analysis was performed on the 391 CRF02_AG sequences along with all globally sampled CRF02_AG sequences (N = 3,302) as references. Phylodynamic and phylogeographic analysis was performed to the largest CRF02_AG monophyletic cluster by a Bayesian method in BEAST v1.8.0 and by reconstructing ancestral states using the criterion of parsimony in Mesquite v3.4, respectively.Results: The HIV-1 CRF02_AG prevalence differed across Spanish autonomous communities we sampled from (p &lt; 0.001). Phylogenetic analysis revealed that 52.7% of the CRF02_AG sequences formed 56 monophyletic clusters, with a range of 2–79 sequences. The CRF02_AG regional dispersal differed across Spain (p = 0.003), as suggested by monophyletic clustering. For the largest monophyletic cluster (subepidemic) (N = 79), 49.4% of the clustered sequences originated from Madrid, while most sequences (51.9%) had been obtained from men having sex with men (MSM). Molecular clock analysis suggested that the origin (tMRCA) of the CRF02_AG subepidemic was in 2002 (median estimate; 95% Highest Posterior Density-HPD interval: 1999–2004). Additionally, we found significant clustering within the CRF02_AG subepidemic according to the ethnic origin.Conclusion: CRF02_AG has been introduced as a result of multiple introductions in Spain, following regional dispersal in several cases. We showed that CRF02_AG transmissions were mostly due to regional dispersal in Spain. The hot-spot for the largest CRF02_AG regional subepidemic in Spain was in Madrid associated with MSM transmission risk group. The existence of subepidemics suggest that several spillovers occurred from Madrid to other areas. CRF02_AG sequences from Hispanics were clustered in a separate subclade suggesting no linkage between the local and Hispanic subepidemics

Sea surface salinity and wind speed retrievals using gnss-r and l-band microwave radiometry data from fmpl-2 onboard the fsscat mission

The Federated Satellite System mission (FSSCat), winner of the 2017 Copernicus Masters Competition and the first ESA third-party mission based on CubeSats, aimed to provide coarse-resolution soil moisture estimations and sea ice concentration maps by means of the passive microwave measurements collected by the Flexible Microwave Payload-2 (FMPL-2). The mission was successfully launched on 3 September 2020. In addition to the primary scientific objectives, FMPL-2 data are used in this study to estimate sea surface salinity (SSS), correcting for the sea surface roughness using a wind speed estimate from the L-band microwave radiometer and GNSS-R data themselves. FMPL-2 was executed over the Arctic and Antarctic oceans on a weekly schedule. Different artificial neural network algorithms have been implemented, combining FMPL-2 data with the sea surface temperature, showing a root-mean-square error (RMSE) down to 1.68 m/s in the case of the wind speed (WS) retrieval algorithms, and RMSE down to 0.43 psu for the sea surface salinity algorithm in one single pass.This work was supported by the 2017 ESA S3 Challenge and Copernicus Masters Overall Winner award (“FSSCat” project). This work was (partially) sponsored by project SPOT: Sensing with Pioneering Opportunistic Techniques grant RTI2018-099008-B-C21/AEI/10.13039/501100011033, and by the Unidad de Excelencia Maria de Maeztu MDM-2016-0600. Joan Francesc Munoz-Martin received support in the form of a grant for the recruitment of early-stage research staff FI-DGR 2018 from the AGAUR—Generalitat de Catalunya (FEDER), Spain

The Flexible Microwave Payload-2: A SDR-Based GNSS-Reflectometer and L-Band Radiometer for CubeSats

This article presents the FMPL-2 on board the FSSCat mission, the 2017 ESA Small Sentinel Satellite Challenge and overall Copernicus Masters Competition winner. FMPL-2 is a passive microwave instrument based on a software-defined radio that implements a conventional global navigation satellite system - Reflectometer and an L-band radiometer, occupying 1 U of a 6 U CubeSat. The article describes the FSSC at mission context, the payload design and implementation phases, the tests results in a controlled environment, and finally the calibration algorithms applied to the downloaded data in order to extract the appropriate geophysical parameters: sea-ice coverage, sea-ice thickness (SIT), and low-resolution soil moisture. This article covers the overall payload design, from a high-level block diagram down to single-component specifications from both hardware and software points of view. The main block of the instrument is based on the combination of an FPGA, which virtualizes a dual-core ARM processor, where most of the calculus are performed, and a software-defined radio module, in charge of I/Q data demodulation. The article also explains the design and implementation of a signal conditioning board required for the correct operation and calibration of both instruments.This work was supported in part by the ESA S3 challenge award (FSSCat project) 2017 Copernicus Masters overall winner [44], in part by the Spanish Ministry of Economy and Competitiveness, by the Spanish Ministry of Science, Innovation and Universities, “Sensing with Pioneering Opportunistic Techniques” SPOT under Grant RTI2018-099008-BC21, in part by the de Excelencia Maria de Maeztu MDM-2016-0600, and in part by the ICREA Academia award by the Generalitat de Catalunya

Sea Ice Thickness Estimation Based on Regression Neural Networks Using L-Band Microwave Radiometry Data from the FSSCat Mission

Special issue Polar Sea Ice: Detection, Monitoring and Modeling.-- 20 pages. 10 figures, 2 tables.-- Data used in this study will be publicly and freely available for everyone at the Copernicus system as part of the FSSCat missionSeveral methods have been developed to provide polar maps of sea ice thickness (SIT) from L-band brightness temperature (TB) and altimetry data. Current process-based inversion methods to yield SIT fail to address the complex surface characteristics because sea ice is subject to strong seasonal dynamics and ice-physical properties are often non-linearly related. Neural networks can be trained to find hidden links among large datasets and often perform better on convoluted problems for which traditional approaches miss out important relationships between the observations. The FSSCat mission launched on 3 September 2020, carries the Flexible Microwave Payload-2 (FMPL-2), which contains the first Reflected Global Navigation Satellite System (GNSS-R) and L-band radiometer on board a CubeSat—designed to provide TB data on global coverage for soil moisture retrieval, and sea ice applications. This work investigates a predictive regression neural network approach with the goal to infer SIT using FMPL-2 TB and ancillary data (sea ice concentration, surface temperature, and sea ice freeboard). Two models—covering thin ice up to 0.6 m and full-range thickness—were separately trained on Arctic data in a two-month period from mid-October to the beginning of December 2020, while using ground truth data derived from the Soil Moisture and Ocean Salinity (SMOS) and Cryosat-2 missions. The thin ice and the full-range models resulted in a mean absolute error of 6.5 cm and 23 cm, respectively. Both of the models allowed for one to produce weekly composites of Arctic maps, and monthly composites of Antarctic SIT were predicted based on the Arctic full-range model. This work presents the first results of the FSSCat mission over the polar regions. It reveals the benefits of neural networks for sea ice retrievals and demonstrates that moderate-cost CubeSat missions can provide valuable data for applications in Earth observationThis work was supported by 2017 ESA S3 challenge and Copernicus Masters overall winner award (“FSSCat” project), and has been (partially) sponsored by the project SPOT: Sensing with Pioneering Opportunistic Techniques grant RTI2018-099008-B-C21/AEI/10.13039/501100011033, and by the Unidad de Excelencia Maria de Maeztu MDM-2016-0600. This work has also been (partially) sponsored by the Spanish Ministry of Science and Innovation through the project ESP2017-89463-C3, and by the Centro de Excelencia Severo Ochoa (CEX2019-000928-S), and by the CSIC Plataforma Temática Interdisciplinar de Teledetección (PTI-Teledetect). Christoph Herbert receives support from “la Caixa” Foundation (ID 100010434) with the fellowship code LCF/BQ/DI18/11660050, and funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No. 713673; Joan Francesc Munoz-Martin receives support from the grant for recruitment of early-stage research staff FI-DGR 2018 of the AGAUR—Generalitat de Catalunya (FEDER), Spain; David Llavería receives support from a FPU fellowship from the Spanish Ministry of Education FPU18/06107Peer reviewe

Soil Moisture Retrieval Using the FMPL-2/FSSCat GNSS-R and Microwave Radiometry Data

2021 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), 11-16 July 2021, Brussels, BelgiumThis work presents the first scientific results over land from the Flexible Microwave Payload −2 (FMPL-2), onboard the FSSCat mission. FMPL-2 is composed of an L-band microwave radiometer and a Global Navigation Satellite System - Reflectometer (GNSS-R). Two separate ANNs models are trained using the first three months of collected data of both observations, with the objective to retrieve global soil moisture maps. The first network addresses the coarsely-resolved FMPL-2 antenna footprint in a downscaling approach. Predicted values resulted in good agreement with those obtain from the SMAP mission, with an error smaller than 9.6%, and a bias smaller than 0.001 m 3 /m 3 . The second network is implemented to estimate soil moisture exclusively on GNSS-R data. In this second case, the combination of multiple GNSS-R measurements in a single track allows to retrieve soil moisture data with an error standard deviation with respect to SMAP lower than 0.056 m 3 /m 3 , with a bias smaller than 0.0007 m 3 /m 3Peer reviewe

Implementation of a testbed for GNSS-R payload performance evaluation

The functional performance of space-borne instruments must be validated on ground before and after satellite integration. The effects of radio-frequency interference are also becoming more important, even in protected bands for earth observation. In this article, a GNSS and GNSS-R signal simulator is developed as part of a testbed of GNSS receivers and GNSS-R payloads' performance in high dynamics, and to study the effects of RFI in the GNSS-R observables. This article describes the different concepts and key enabling techniques that have been developed to support this project.This work was supported in part by Spanish Ministerio de Ciencia, Innovación y Universidades and EU ERDF under Project RTI2018-099008-B-C21, in part by the Sensing With Pioneering Opportunistic Techniques under Grant MDM-2016-0600, in part by the Maria de Maeztu Excellence Research Units CommSensLab, and in part by Spanish Ministerio de Economía y Competitividad (MINECO/FEDER)