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The Microwave Interferometric Reflectometer (MIR) is an airborne GNSS-R instrument developed by Universitat Politècnica de Catalunya. In 2018, it was flown twice over the agricultural Yanco area, New South Wales, Australia, once after a very dry period, and a further time the day after a strong rain event. This rain event resulted in many crop fields being entirely flooded, producing a saturation in the GNSS-R reflectivity value. In this work, the received data set is processed to identify the optimum integration time with the goal to minimize pixel blurring. This issue is assessed for airborne conditions, and then extra-polated to the spaceborne case. The presented results show that the blurring of the GNSS waveform is produced even from an airborne sensor with short integration times. Following the determination of an optimal integration time for the platform in use, the surface roughness term in the reflectivity equation can be isolated due to the signal saturation during very wet surface conditions. The final results from the two channels (L1 C/A and L5) are subsequently presented. In this case, it is shown that most reflectivity variations in GNSS-R measurements are linked to surface roughness and Speckle noise fluctuations rather than soil moisture changes.

The Remote sensing and Interference detector with radiomeTry and vegetation Analysis (RITA) payload is one of the Remote Sensing payloads selected by the 2nd GRSS Student Grand Challenge in 2019 to fly on board of a 3U satellite that is being developed at the National space Science and Technology Center (NSSTC), United Arab Emirates University. RITA has been designed as an academic mission with a strong focus on Earth Observation techniques and technologies. This payload is equipped with a Software-Defined Radio for microwave radiometry and RFI detection, a hyperspectral camera (25 bands from 600 to 975 nm), and a LoRa transceiver, which will work in tandem to produce vegetation-related measurements with improved accuracy. Soil moisture measurements, for example, will be derived from a Total Power Microwave Radiometer working at L-band and Normalized Difference Vegetation Index (NDVI) measurements in a technique known as Pixel Downscaling. In this work, recent advances in the payload design will be presented, as well as a more in depth mission analysis.

The Flexible Microwave Payload -2 is the microwave remote sensing payload of the FSSCat mission. The instrument is the outcome of years of work of the Universitat Politécnica de Catalunya Passive Remote Sensing Laboratory, and the NanoSat-Lab. The FSSCat mission was launched on board the Vega VV16, on September the 3 rd , 2020. The instrument was executed for the very first time on September the 16 th , 2020, and it was commissioned less than two weeks later. This extended abstract presents the geo-located FMPL-2 measurements, which consist of a Global Navigation Satellite System - Reflectometer and an L-band radiometer. The performance of the instrument and preliminary level 1C results are presented, showing that CubeSats can to perform passive microwave remote sensing scientific missions. This work was supported by 2017 ESA S3 challenge and Copernicus Masters overall winner award (“FSSCat” project). This work has been (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.

2021 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), 11-16 July 2021, Brussels, Belgium, FSSCat, the “Federated Satellite Systems/ 3 Cat-5” mission was the winner of the 2017 ESA S^3 (Sentinel Small Satellite) Challenge and overall winner of the Copernicus Masters competition. FSSCat consists of two 6 unit cubesats carrying on board UPC's Flexible Microwave Payload - 2 (FMPL-2), an L-band microwave radiometer and GNSS-Reflectometer implemented in a software defined radio, and Cosine's HyperScout-2 visible and near infrared + thermal infrared hyperspectral imager, enhanced with PhiSat-1, a on board Artificial intelligence experiment for cloud detection. Both spacecrafts include optical and UHF inter-satellite links technology demonstrators, provided by Golbriak Space and UPC, respectively. This paper describes the mission, and the main scientific results of the FMPL-2 obtained during the first three months of the mission, notably the sea ice concentration and thickness, and the downscaled soil moisture products over the Northern hemisphere

2021 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), 11-16 July 2021, Brussels, Belgium.-- 4 pages, 4 figures, Knowledge about sea ice concentration and extent in polar regions is of great interest both for economic interests, and as a proxy of the climate change. Retrieved maps are based on data from microwave radiometers, which are currently provided by large satellite missions. Nowadays, CubeSats have proven to be a cost-effective alternative. Due to their low cost, they can be launched in large constellations to obtain high spatial coverage and daily revisit. This study presents a neural network approach to generate sea ice concentration and sea ice extension maps using the L-band microwave radiometer, and the GNSS-Reflectometer data from the FMPL-2 instrument onboard 3 Cat-5/A, one of the two CubeSats of the FSSCat mission. The results obtained during the first 2 months of the mission are presented

Vegetation canopy height is one of the important remote sensing parameters related to forests’ structure, and it can be related to the biomass and the carbon stock. Global Navigation Satellite System - Reflectometry (GNSS-R) has proven capable to retrieve vegetation information at a moderate resolution from space (20-65 km) using L1 C/A signals. In this study, data retrieved by the airborne Microwave Interferometric Reflectometer (MIR) GNSS-R instrument at L1 and L5 are compared to the Global Forest Canopy Height product, with a spatial resolution of 30 m. This work analyzes the waveforms measured at both bands, and the correlation of the waveform width and the reflectivity values to the canopy height product. A neural network algorithm is used for the retrieval, showing that the combination of the reflectivity and the waveform width allows to estimate the canopy height information at a very high resolution, with a root-mean-square error of 4.25 m and 4.07 m at L1 and L5, respectively, which is an error about 14% of the actual canopy height.

Special issue Applications of GNSS Reflectometry for Earth Observation II.-- 19 pages, 17 figures, 4 tables, supplementary material https://doi.org/10.3390/rs13061139.-- Data used in this study will be publicly and freely available for everyone through the Copernicus system as part of the FSSCat mission, CubeSat-based Earth Observation missions have emerged in recent times, achieving scientifically valuable data at a moderate cost. FSSCat is a two 6U CubeSats mission, winner of the ESA S3 challenge and overall winner of the 2017 Copernicus Masters Competition, that was launched in September 2020. The first satellite, 3Cat-5/A, carries the FMPL-2 instrument, an L-band microwave radiometer and a GNSS-Reflectometer. This work presents a neural network approach for retrieving sea ice concentration and sea ice extent maps on the Arctic and the Antarctic oceans using FMPL-2 data. The results from the first months of operations are presented and analyzed, and the quality of the retrieved maps is assessed by comparing them with other existing sea ice concentration maps. As compared to OSI SAF products, the overall accuracy for the sea ice extent maps is greater than 97% using MWR data, and up to 99% when using combined GNSS-R and MWR data. In the case of Sea ice concentration, the absolute errors are lower than 5%, with MWR and lower than 3% combining it with the GNSS-R. The total extent area computed using this methodology is close, with 2.5% difference, to those computed by other well consolidated algorithms, such as OSI SAF or NSIDC. The approach presented for estimating sea ice extent and concentration maps is a cost-effective alternative, and using a constellation of CubeSats, it can be further improved, This work was supported by 2017 ESA S3 challenge and Copernicus Masters overall winner award (“FSSCat” project). this work has been (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. 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). David Llavería receives support from a FPU fellowship from the Spanish Ministry of Education FPU18/06107.; 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; C.H. receives support of a fellowship 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

The Remote sensing and Interference detector with radiomeTry and vegetation Analysis (RITA) payload is one of the Remote Sensing payloads selected by the 2nd GRSS Student Grand Challenge to fly on board of a 3U satellite from the United Arab Emirates' National Space Science and Technology Center (NSSTC). The main objectives of RITA are to perform microwave radiometry measurements at L-band, vegetation analysis using a hyper-spectral camera, Radio-Frequency Interference (RFI) detection and classification, and a technology demonstration of sensor networks using a custom LoRa transceiver. Radiometry measurements, RFI detection, and the LoRa experiment will be performed using a Software-Defined Radio (SDR) with a frontend designed as a modified version of the Flexible Microwave Payload 1 (FMPL-1) used in the 3Cat-4 mission, whereas an hyper-spectral camera will be used primarily for vegetation measurements. This work discusses the description and design of the payload, and emphasizes on the techniques used for the generation of the scientific outcome.

FSSCAT mission was the 2017 ESA Sentinel Small Satellite (S^3) Challenge winner, and the Copernicus masters competition overall winner, and it will be launched in late March 2020. FSSCAT data will provide soil moisture data, sea ice cover and coarse resolution sea ice thickness. FSSCat will be launched for Kourou Space port on June 18 th , 2020, 10:51 PM local time. MOSAiC (Multidisciplinary drifting Observatory for the Study of Arctic Climate) campaign is a one-year long field experiment to study the climate system and the impact of the climate change in the Arctic sea. GNSS-R data from the second leg has been received recently. At the conference the first results of the FMPL-2 payload (combined GNSS-R and microwave radiometer instrument) on board FSSCat will be presented. Preliminary results on the PYCARO-2 GNSS-R instrument in MOSAIC, and model results fed with in-situ auxiliary data are presented in this paper.

© 2022 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. As compared to the using L1C/A signals, L5/E5a Global Navigation Satellite System - Reflectometry (GNSS-R), gives improved resolution over the Earth's surface due to the sharper auto-correlation function. Furthermore, the larger transmitted power (+3dB with respect to L1 C/A), and correlation gain (+40dB) allows the reception of weaker reflected signals. If high directivity antennas are used, very short incoherent integration times are needed to have enough signal-to-noise (SNR) ratios, allowing the reception of multiple specular reflection points such as crest of consecutive waves without the blurring induced by long incoherent integration times. This study presents for the first time experimental evidence of the wind and swell waves signatures in the GNSS-R waveforms, and compares them with models.

© 2022 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. Global Navigation Satellite Systems Reflected (GNSS-R) signals exhibit an incoherent and a coherent components [1], [2]. Current models assume that one or the other are dominant, and the calibration, and geophysical parameter retrieval (eg. wind speed, soil moisture ...) are developed accordingly. Even the presence itself of the coherent component of a GNSS reflected signal has been a matter of discussion in the last years. In this work, the method used in [3] to separate the leakage of the direct signal from the reflected one is applied to a set of GNSS signals reflected collected over the ocean by the MIR [4], [5], an airborne dual-band (L1/E1 and L5/E5a), multi-constellation (GPS and Galileo) GNSS-R instrument with two 19-elements array with 4 beam-steered each. The results presented demonstrate the feasibility of the proposed technique to untangle the coherent and incoherent components in GNSS reflected signals. This technique allows the processing of these components separately, which will increase the calibration accuracy (as today both are mixed together), and allows high resolution applications since the spatial resolution of the coherent component is determined by the size of the first Fresnel zone [6] (300-500 meters from a LEO satellite), and not by the size of the glistening zone (~25 km from a LEO satellite). This work was supported by the Spanish Ministry of Science, Innovation and Universities, “Sensing with Pio- neering Opportunistic Techniques”, grant RTI2018-099008- B-C21, and the grant for recruitment of early-stage research staff FI-DGR 2015 and 2018 of the AGAUR - Generalitat de Catalunya (FEDER)

Weather forecast relies to a large extent on data acquired by satellite. LEO polar satellites provide global coverage, but poor spatial resolution. GEO satellites provide a better coverage and revisit time, at expenses of poorer spatial resolution. LEO constellations of small satellites offer the promise of global coverage with good spatial resolution and revisit time. However, hosted payloads on aircrafts offer the potential of very high resolution and very low revisit time for regional applications. In this work, the idea of equipping commercial airliners with low-cost Global Navigation Satellite System - Reflectometer (GNSS-R) receivers is explored, with emphasis on real-world data and the implications the expected scientific yield would offer. This work has received funding from project Spanish Ministerio de Ciencia, Innovacion y Universidades and EU ERDF project ref. RTI2018-099008-B-C21 ”SENSING WITH PIONEERING OPPORTUNISTIC TECHNIQUES,“ , and support grant MDM-2016-0600 to “María de Maeztu Excellence Units” CommSensLab, from Spanish Ministerio de Economía y Competitividad (MINECO/FEDER).

The FSSCat mission is a two nano-satellite Earth Observation mission based on 6-unit CubeSats. This paper is focused on the description of one of the remote sensing payloads: the Flexible Microwave Payload 2 (FMPL-2), on board the 3 Cat-5/A. The payload design is based on a Software Defined Radio, aiming to demonstrate the capabilities of nano-satellites to provide valuable scientific data. Two different instruments are integrated into a single payload: a multi-constellation (GPS and Galileo) Global Navigation Satellite System Reflectometer (GNSS-R), and a Total Power Radiometer (TPR) with Radio Frequency Interference (RFI) detection and mitigation capabilities. This paper presents the payload design, and the tests conducted during the qualification campaign. This work was supported by the ESA S3 challenge award (FSSCat project) 2017 Copernicus Masters overall winner, by the Spanish Ministry of Economy and Competitiveness, by the Spanish Ministry of Science, Innovation and Universities, ”Sensing with Pioneering Opportunistic Techniques”, grant RTI2018-099008-B-C21, by the Unidad de Excelencia Maria de Maeztu MDM-2016-0600, and by the ICREA Academia award by the Generalitat de Catalunya.

The Flexible Microwave Payload 2 (FMPL-2) is a Remote Sensing payload carried on board 3 Cat-5/A, one of the two 6-unit CubeSats of the FSSCat mission. FMPL-2 is a payload based on a Software Defined Radio (SDR), integrating two instruments in a single platform: a multi-constellation (GPS and Galileo) Global Navigation Satellite System Reflectometer (GNSS-R), and a Total Power Radiometer (TPR) with Radio Frequency Interference (RFI) detection and mitigation capabilities. This paper focuses on the description of the software developed for the platform, with a detailed description on the optimizations used for the two instruments. This work was supported by the ESA S3 challenge award (FSSCat project) 2017 Copernicus Masters overall winner, by the Spanish Ministry of Economy and Competitiveness, by the Spanish Ministry of Science, Innovation and Universities, ’’Sensing with Pioneering Opportunistic Techniques", grant RTI2018-099008-B-C21, by the Unidad de Excelencia Maria de Maeztu MDM-2016-0600, and by the ICREA Academia award by the Generalitat de Catalunya.

The 3 Cat-4 mission aims to demonstrate the capabilities of nano-satellites plus the versatility of a Software Defined Radio for passive Earth Observation. Three different microwave payloads are integrated into a single unit CubeSat platform: a multi-constellation (GPS and Galileo) and a dual-band (L1 and L2) Global Navigation Satellite System - Reflectometer receiver, a total power radiometer including a novel Radio Frequency Interference (RFI) detection and mitigation technique, and an Automatic Identification System receiver for vessels tracking. Being able to validate these technologies in a CubeSat enables their fast adoption as hosted payloads or in more performing dedicated platforms in the future. This paper shows a novel approach for embedding multiple passive microwave payloads in a single platform.

FSSCAT is an innovative mission concept consisting of two federated 6U Cubesats in support of the Copernicus Land and Marine Environment services. The first CubeSat carries the Flexible Microwave Payload-2 (FMPL-2), a dual microwave payload (a GNSS-Reflectometer and an L-band radiometer with interference detection/mitigation), and the second one a hyper-spectral optical payload. The combined use of these payloads will allow to measure soil moisture, ice extent, and ice thickness, and to detect melting ponds over ice. FSSCAT also includes radio and optical inter-satellite links to test some of the techniques and technologies for the upcoming satellite federations. FSSCAT will be the precursor of a constellation of federated small satellites for Earth observation achieving high temporal resolution and moderate spatial resolution in a cost-effective manner.