7 research outputs found

    Feasibility of GNSS-R ice sheet altimetry in Greenland using TDS-1

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    Radar altimetry provides valuable measurements to characterize the state and the evolution of the ice sheet cover of Antartica and Greenland. Global Navigation Satellite System Reflectometry (GNSS-R) has the potential to complement the dedicated radar altimeters, increasing the temporal and spatial resolution of the measurements. Here we perform a study of the Greenland ice sheet using data obtained by the GNSS-R instrument aboard the British TechDemoSat-1 (TDS-1) satellite mission. TDS-1 was primarily designed to provide sea state information such as sea surface roughness or wind, but not altimetric products. The data have been analyzed with altimetric methodologies, already tested in aircraft based experiments, to extract signal delay observables to be used to infer properties of the Greenland ice sheet cover. The penetration depth of the GNSS signals into ice has also been considered. The large scale topographic signal obtained is consistent with the one obtained with ICEsat GLAS sensor, with differences likely to be related to L-band signal penetration into the ice and the along-track variations in structure and morphology of the firn and ice volumes The main conclusion derived from this work is that GNSS-R also provides potentially valuable measurements of the ice sheet cover. Thus, this methodology has the potential to complement our understanding of the ice firn and its evolution.Peer ReviewedPostprint (published version

    A generic level 1 simulator for spaceborne GNSS-R missions and application to GEROS-ISS ocean reflectometry

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    ©2017 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.In the past decade Global Navigation Satellites System Reflectometry (GNSS-R) has emerged as a new technique for earth remote sensing for various applications, such as ocean altimetry and sea state monitoring. After the success of the GNSS-R demonstrator payloads aboard the UK-DMC or TDS-1 satellites; at present, there are several missions planned to carry GNSS reflectometers. The GNSS rEflectometry, Radio Occultation, and Scatterometry onboard International Space Station (GEROS-ISS) is an innovative ISS experiment exploiting GNSS-R technique to measure key parameters of ocean, land, and ice surfaces. For GEROS-ISS mission, the European Space Agency (ESA) supported the study of GNSS-R assessment of requirements and consolidation of retrieval algorithms (GARCA). For this, it was required to accurately simulate the GEROS-ISS measurements including the whole range of parameters affecting the observation conditions and the instrument, which is called GEROS-SIM. To meet these requirements, the PAU/PARIS end-to-end performance simulator (P2^{2}EPS) previously developed by UPC BarcelonaTech was used as the baseline building blocks for the level 1 (L1) processor of GEROS-SIM. P2^{2}EPS is a flexible tool, and is capable of systematically simulating the GNSS-R observations for spaceborne GNSS-R missions. Thanks to the completeness and flexibility, the instrument-to-L1 data module of GEROS-SIM could be implemented by proper modification and update of P2^{2}EPS. The developed GEROS-SIM was verified and validated in the GARCA study as comparing to the TDS-1 measurements. This paper presents the design, implementation, and results of the GEROS-SIM L1 module in a generic way to be applied to GNSS-R instruments.Peer ReviewedPostprint (author's final draft

    Sea target detection using spaceborne GNSS-R delay-doppler maps: theory and experimental proof of concept using TDS-1 data

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    © 2017 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.This study addresses a novel application of global navigation satellite system-reflectometry (GNSS-R) delay-Doppler maps (DDMs), namely sea target detection. In contrast with other competing remote sensing technologies, such as synthetic aperture radar and optical systems, typically exploited in the field of sea target detection, GNSS-R systems could be employed as satellite constellations, so as to fulfill the temporal requirements for near real-time ships and sea ice sheets monitoring. In this study, the revisit time offered by GNSS-R systems is quantitatively evaluated by means of a simulation analysis, in which three different realistic GNSS-R missions are simulated and analyzed. Then, a sea target detection algorithm from spaceborne GNSS-R DDMs is described and assessed. The algorithm is based on a sea clutter compensation step and uses an adaptive threshold to take into account spatial variations in the sea background and/or noise statistics. Finally, the sea target detector algorithm is tested and validated for the first time ever using experimental GNSS-R data from the U.K. TechDemoSat-1 dataset. Performance is assessed by providing the receiver operating characteristic curves, and some preliminary experimental results are presented.Peer ReviewedPostprint (published version

    Sea ice detection using GNSS-R data from UK TDS-1

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    This work demonstrates a methodology to detect sea ice presence over the Arctic and Antarctic regions using Global Navigation Satellite Systems (GNSS)-Reflectometry (GNSS-R) data obtained with the UK TDS-1 satellite. The algorithm is based on estimating the degree of coherence of the received GNSS reflected waveform or Delay-Doppler Map (DDM). While at open ocean conditions, the scattered signal follows the diffuse scattering model, over flat sea ice it follows the coherent scattering model. In order to measure the degree of coherence of the received waveform or DDM, a correlation with the clean Woodward Ambiguity Function (WAF) is performed. The more similar the received signal is to the WAF, the more coherent is the scattering, and consequently, the more likely a flat sea ice surface is involved. In order to assess the performance of the proposed estimator a probabilistic study based on a Bayesian approach is performed, using the OSISAF Sea Ice Concentration (SIC) maps as ground truth. A probability of detection of 97%, a probability of false alarm of 2%, and a probability of error of 2.5% are the best results obtained for the Arctic region.Peer Reviewe

    Sea ice detection using GNSS-R data from UK TDS-1

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    Sea ice detection using GNSS-R data from UK TDS-1

    No full text
    This work demonstrates a methodology to detect sea ice presence over the Arctic and Antarctic regions using Global Navigation Satellite Systems (GNSS)-Reflectometry (GNSS-R) data obtained with the UK TDS-1 satellite. The algorithm is based on estimating the degree of coherence of the received GNSS reflected waveform or Delay-Doppler Map (DDM). While at open ocean conditions, the scattered signal follows the diffuse scattering model, over flat sea ice it follows the coherent scattering model. In order to measure the degree of coherence of the received waveform or DDM, a correlation with the clean Woodward Ambiguity Function (WAF) is performed. The more similar the received signal is to the WAF, the more coherent is the scattering, and consequently, the more likely a flat sea ice surface is involved. In order to assess the performance of the proposed estimator a probabilistic study based on a Bayesian approach is performed, using the OSISAF Sea Ice Concentration (SIC) maps as ground truth. A probability of detection of 97%, a probability of false alarm of 2%, and a probability of error of 2.5% are the best results obtained for the Arctic region.Peer Reviewe

    Contributions to land, sea, and sea ice remote sensing using GNSS-reflectometry

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    This PhD thesis researches the use of passive remote sensing techniques using signals transmitted from the navigation satellites (GNSS) in order to retrieve different geophysical parameters. The thesis consists of two different parts without taking into account the introduction, the state of the art and the conclusions. The first part analyzes the Interference Pattern Technique (IPT), which was previously used in another PhD thesis, and proposes some key improvements. First, the addition of horizontal polarization to the existing vertical polarization is proposed. Then, the retrieval of soil moisture is studied using the horizontal polarization only and combining both polarizations to correct for the surface roughness effects. It is also demonstrated that the phase difference between the two interference patterns is directly related to soil moisture content. A field campaign was conducted in Australia to test empirically all the theoretical developments and algorithms. Secondly, the possibility of measuring Significant Wave Height (SWH) and Mean Sea Surface Level (MSSL) using the IPT is studied. A three month field campaign over coastal sea is devoted to that study. The SWH retrieval is a new estimation algorithm based on measuring the point where the interference pattern loses coherence. The MSSL retrieval is based on the estimation of the IPT oscillation frequency, testing different spectral estimators to improve the accuracy. Since the IPT is limited in coverage due to its static requirements, the research conducted in this thesis migrated to scatterometric GNSS-R techniques. The main goal that migration was to increase coverage of the different GNSS-R instruments. Therefore, the second part of this thesis analyzes the applicability of a scatterometric technique from different platforms: ground-based (mobile and fixed), airborne, and spaceborne. The ground-based still platforms have allowed to develop a soil moisture retrieval algorithm. The ground-based moving platforms have extended the validity of that algorithm. Airborne platforms have been used to study the reflected electric field statistics when the surface reflecting surface is varying (smooth or rough land, and sea). They have also been used to develop different algorithms to measure the coherent and incoherent scattered components depending on the data structure (real-data or complex data). Coherent reflectivity measured from airborne platforms has been compared to other techniques such microwave radiometry, which is highly used in the soil moisture retrieval from spaceborne sensors, and other sensors using optical, multispectral and thermal frequency bands. These relationships between microwave radiometry and GNSS-R measurements suggests the potential synergy of both techniques. A sea ice detection algorithm is also developed using scatterometric GNSS-R data from the UK TDS-1 mission. This algorithm is based on measuring the degree of coherence of the reflected waveform. Finally, a field campaign was conducted to study the effect of vegetation on the GNSS signals that pass through it in order to take into account and correct the effect of vegetation in the GNSS-R data and in the soil moisture retrieval algorithms.Aquesta tesi doctoral aprofundeix en el coneixement de les tècniques de teledetecció passives utilitzant senyals emesos pels satèl·lits de navegació (GNSS) amb l'objectiu de recuperar diferents paràmetres geofísics del terreny. La tesi conté dues parts ben diferenciades a banda de la introducció, estat de l'art i conclusions. La primera part analitza la tècnica coneguda com a patró d'interferències, utilitzada prèviament en una altra tesi doctoral, i proposa certes millores per la seva aplicabilitat. En primer lloc es decideix afegir polarització horitzontal a la ja existent polarització vertical, i s'estudia la recuperació d'humitat del sòl utilitzant només polarització horitzontal i combinant les dues polaritzacions per corregir els efectes de la rugositat del terreny. A continuació es demostra que la mesura de desfasament entre els dos patrons d'interferència està directament relacionada amb la humitat del terreny. Es va realitzar una campanya de mesures a Austràlia per provar empíricament tots els desenvolupaments teòrics i algorismes proposats. En segon lloc s'analitza l'aplicabilitat del patró d'interferències en la mesura de l'altura de les onades (SWH) i del nivell del mar (MSSL), tots dos de forma precisa. L'estimació de l'alçada de les onades és un procés totalment nou basat en mesurar el punt on el patró d'interferències perd la coherència. L'estimació del nivell del mar es basa en l'anàlisi espectral del patró d'interferències provant diferents estimadors espectrals. Atès que la tècnica del patró d'interferència està limitada en cobertura per les seves característiques estàtiques, la investigació duta a terme en aquesta tesi doctoral va migrar cap a tècniques GNSS-R escateromètriques. El principal objectiu a assolir va ser el d'augmentar la cobertura dels diferents instruments GNSS-R de mesura. En conseqüència, la segona part d'aquesta tesi analitza l'aplicabilitat d'aquestes tècniques des de diferents plataformes terrestres (mòbils i fixes), aerotransportades i satèl·lit. Les plataformes terrestres fixes han permès derivar algoritmes de recuperació d'humitat i les mòbils estendre la validació d'aquests. Les plataformes aerotransportades s'han utilitzat per mirar l'estadística del camp elèctric reflectit quan la superfície on es reflecteixen els senyals GNSS va variant (terra plana o terra rugosa, i mar). També han servit per desenvolupar diferents algorismes amb l'objectiu de determinar les components coherent i incoherent del senyal reflectit. De la mateixa manera, dades de reflectivitat coherent mesurades des d'aquestes plataformes han estat comparades amb altres tècniques de teledetecció passiva com la radiometria de microones, altament utilitzada en la mesura d'humitat de terreny, i altres sensors òptics, multi-espectrals, i tèrmics. Aquests resultats han permès suggerir la possible sinergia de dades d'ambdues tecnologies. Un algorisme per detectar la presència de gel sobre el mar també ha estat desenvolupat mitjançant l'ús de dades GNSS-R escateromètriques satel·litals de la missió UK TDS-1. Aquest algorisme es basa en mesurar el grau de coherència de la forma d'ona reflectida. Finalment, s'ha realitzat un estudi de l'efecte de la vegetació en els senyals GNSS que la travessen, per tal de poder corregir aquest efecte en els algoritmes de recuperació d'humitat del terreny
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