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Multi‑constellation GNSS interferometric reflectometry for the correction of long-term snow height retrieval on sloping topography / Wei Zhou in GPS solutions, vol 26 n° 4 (October 2022)  

Public [article]  inGPS solutions > vol 26 n° 4 (October 2022) . - n° 140 Titre : Multi‑constellation GNSS interferometric reflectometry for the correction of long-term snow height retrieval on sloping topography Type de document : Article/Communication Auteurs : Wei Zhou, Auteur ; Liangke Huang, Auteur ; Bing Ji, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 140 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] hauteur (coordonnée) [Termes IGN] manteau neigeux [Termes IGN] pente [Termes IGN] Ransac (algorithme) [Termes IGN] rapport signal sur bruit [Termes IGN] réflectométrie par GNSS [Termes IGN] signal GNSS [Termes IGN] système de référence altimétrique [Termes IGN] topographie locale [Termes IGN] transformation en ondelettes [Termes IGN] valeur aberrante [Vedettes matières IGN] Altimétrie Résumé : (auteur) Snow is a key parameter for global climate and hydrological systems. Global Navigation Satellite System interferometric reflectometry (GNSS-IR) has been applied to accurately monitor snow height (SH) with low cost and high temporal–spatial resolution. We proposed an improved GNSS-IR method using detrended signal-to-noise ratio (δSNR) arcs corresponding to multipath reflection tracks with different azimuths. After using wavelet decomposition and random sample consensus, noise with various frequencies for SNR arcs and outliers of reflector height (RH) estimations have been sequentially mitigated to enhance the availability of the proposed method. Thus, a height datum based on the ground RHs retrieved from multi-GNSS SNR data is established to compensate for the influence of topography variation with different azimuths in SH retrieval. The approximately 3-month δSNR datasets collected from three stations deployed on sloping topography were used to retrieve SH and compared with the existing method and in situ measurements. The results show that the root mean square errors of the retrievals derived from the proposed method for the three sites are between 4 and 8 cm, and the corresponding correlation surpasses 0.95 when compared to the reference SH datasets. Additionally, we compare the performance of a retrieval with the existing GNSS-IR Web App, and it shows an improvement in RMSE of about 7 cm. Furthermore, because topography variation has been considered, the average correction of SH retrievals is between 2 and 4 cm. The solution with the proposed method helps develop the applications of the GNSS-IR technique on complex topography. Numéro de notice : A2022-712 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article DOI : 10.1007/s10291-022-01333-0 Date de publication en ligne : 15/09/2022 En ligne : https://doi.org/10.1007/s10291-022-01333-0 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101590 [article]

Ground surface elevation changes over permafrost areas revealed by multiple GNSS interferometric reflectometry / Yufeng Hu in Journal of geodesy, vol 96 n° 8 (August 2022)  

Public [article]  inJournal of geodesy > vol 96 n° 8 (August 2022) . - n° 56 Titre : Ground surface elevation changes over permafrost areas revealed by multiple GNSS interferometric reflectometry Type de document : Article/Communication Auteurs : Yufeng Hu, Auteur ; Ji Wang, Auteur ; Zhenhong Li, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 56 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de géodésie spatiale [Termes IGN] Alaska (Etats-Unis) [Termes IGN] analyse diachronique [Termes IGN] dégel [Termes IGN] données Galileo [Termes IGN] données GLONASS [Termes IGN] pergélisol [Termes IGN] rapport signal sur bruit [Termes IGN] réflecteur [Termes IGN] réflectométrie par GNSS [Termes IGN] signal GNSS [Termes IGN] surface du sol [Termes IGN] variation saisonnière Résumé : (auteur) Ground subsidence and uplift caused by the annual thawing and freezing of the active layer are important variables in permafrost studies. Global positioning system interferometric reflectometry (GPS-IR) has been successfully applied to retrieve the continuous ground surface movements in permafrost areas. However, only GPS signals were used in previous studies. In this study, using multiple global navigation satellite system (GNSS) signal-to-noise ratio (SNR) observations recorded by a GNSS station SG27 in Utqiaġvik, Alaska during the period from 2018 to 2021, we applied multiple GNSS-IR (multi-GNSS-IR) technique to the SNR data and obtained the complete and continuous ground surface elevation changes over the permafrost area at a daily interval in snow-free seasons in 2018 and 2019. The GLONASS-IR and Galileo-IR measurements agreed with the GPS-IR measurements at L1 frequency, which are the most consistent measurements among all multi-GNSS measurements, in terms of the overall subsidence trend but clearly showed periodic noises. We proposed a method to reconstruct the GLONASS- and Galileo-IR elevation changes by specifically grouping and fitting them with a composite model. Compared with GPS L1 results, the unbiased root mean square error (RMSE) of the reconstructed Galileo measurements reduced by 50.0% and 42.2% in 2018 and 2019, respectively, while the unbiased RMSE of the reconstructed GLONASS measurements decreased by 41.8% and 25.8% in 2018 and 2019, respectively. Fitting the composite model to the combined multi-GNSS-IR, we obtained seasonal displacements of − 3.27 ± 0.13 cm (R2 = 0.763) and − 10.56 ± 0.10 cm (R2 = 0.912) in 2018 and 2019, respectively. Moreover, we found that the abnormal summer heave was strongly correlated with rain events, implying hydrological effects on the ground surface elevation changes. Our study shows the feasibility of multi-GNSS-IR in permafrost areas for the first time. Multi-GNSS-IR opens up a great opportunity for us to investigate ground surface movements over permafrost areas with multi-source observations, which are important for our robust analysis and quantitative understanding of frozen ground dynamics under climate change. Numéro de notice : A2022-606 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s00190-022-01646-5 Date de publication en ligne : 13/08/2022 En ligne : https://doi.org/10.1007/s00190-022-01646-5 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101385 [article]

Coastal observation of sea surface tide and wave height using opportunity signal from Beidou GEO satellites: analysis and evaluation / Feng Wang in Journal of geodesy, vol 96 n° 4 (April 2022)  

Public [article]  inJournal of geodesy > vol 96 n° 4 (April 2022) . - n° 17 Titre : Coastal observation of sea surface tide and wave height using opportunity signal from Beidou GEO satellites: analysis and evaluation Type de document : Article/Communication Auteurs : Feng Wang, Auteur ; Dongkai Yang, Auteur ; Guodong Zhang, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 17 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géodésie spatiale [Termes IGN] Chine [Termes IGN] données altimétriques [Termes IGN] données marégraphiques [Termes IGN] hauteurs de mer [Termes IGN] méthode de Monte-Carlo [Termes IGN] modèle géométrique [Termes IGN] rapport signal sur bruit [Termes IGN] récepteur GNSS [Termes IGN] réflectométrie par GNSS [Termes IGN] signal BeiDou [Termes IGN] surface de la mer [Termes IGN] vague Résumé : (auteur) In this paper, the methods retrieving tide and SWH using reflected BeiDou GEO satellite signals are proposed, and a data-driven method is proposed to calibrate sea state bias of the retrieved tide. In addition, an estimator combining multi-satellite observation based on linear unbiased minimum variance (LUMV) is developed to improve the retrieved precision. The B1I signal experiments in Qingdao and Shenzhen show after calibrating sea state influence using the proposed method, the root-mean-square error (RMSE) could fall to 0.40 m from 0.45 m, and compared to the single-satellite observation, the multi-satellite observation based on the LUMV estimator could significantly reduce the RMSE of the retrieved tide to 0.16 m. Shenzhen experiment is also used to evaluate the performance of retrieving SWH and the determination coefficient of 0.60 is obtained. This paper also conducts Monte Carlo simulation and experiment to evaluate the altimetry and measuring SWH precision using reflected B3I signal. The simulated results when SNR is over 5 dB, incoherent averaging number is 10000, and the receiver bandwidth is over 45 MHz, the estimated precision of the delay can reach up ∼0.15 m, and the precision of the normalized area ranges from 0.2 to 0.3 m. The B3I experiment show that compared to B1I signal, when the reflected signal from individual satellite is used, the better precision with the RMSE of 0.25 can be obtained, and when combining the measurements from the three satellites using LUMV estimator, the RMSE reduces to 0.16 m. Further, the precision of 0.12 m can be obtained by calibrating the sea state influence. Numéro de notice : A2022-213 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s00190-022-01605-0 Date de publication en ligne : 06/03/2022 En ligne : https://doi.org/10.1007/s00190-022-01605-0 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100050 [article]

GNSS reflectometry global ocean wind speed using deep learning: Development and assessment of CyGNSSnet / Milad Asgarimehr in Remote sensing of environment, vol 269 (February 2022)  

Public [article]  inRemote sensing of environment > vol 269 (February 2022) . - n° 112801 Titre : GNSS reflectometry global ocean wind speed using deep learning: Development and assessment of CyGNSSnet Type de document : Article/Communication Auteurs : Milad Asgarimehr, Auteur ; Caroline Arnold, Auteur ; Tobias Weigel, Auteur ; Chris Ruf, Auteur ; Jens Wickert, Auteur Année de publication : 2022 Article en page(s) : n° 112801 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de géodésie spatiale [Termes IGN] apprentissage profond [Termes IGN] modèle numérique [Termes IGN] réflectométrie par GNSS [Termes IGN] réseau neuronal convolutif [Termes IGN] vent [Termes IGN] vitesse Résumé : (auteur) GNSS Reflectometry (GNSS-R) is a novel remote sensing technique for the monitoring of geophysical parameters using reflected GNSS signals from the Earth's surface. Ocean wind speed monitoring is the main objective of the recently launched Cyclone GNSS (CyGNSS), a GNSS-R constellation of eight microsatellites, launched in late 2016. In this study, the capability of deep learning, especially, for an operational wind speed data derivation from the measured Delay-Doppler Maps (DDMs) is characterized. CyGNSSnet is based on convolutional layers for the feature extraction from bistatic radar cross section (BRCS) DDMs, along with fully connected layers for processing ancillary technical and higher-level input parameters. The best architecture is determined on a validation set and is evaluated over a completely blind dataset from a different time span than that of the training data to validate the generality of the model for operational usage. After a data quality control, CyGNSSnet results in an RMSE of 1.36 m/s leading to a significant improvement by 28% in comparison to the officially operational retrieval algorithm. The RMSE is the lowest among those seen in the literature for any conventional or machine learning-based algorithm. The benefits of the convolutional layers, the advantages and weaknesses of the model are discussed. CyGNSSnet offers efficient processing of GNSS-R measurements for high-quality global ocean winds. Numéro de notice : A2022-079 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article DOI : 10.1016/j.rse.2021.112801 Date de publication en ligne : 23/11/2021 En ligne : https://doi.org/10.1016/j.rse.2021.112801 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99764 [article]

Non-linear GNSS signal processing applied to land observation with high-rate airborne reflectometry / Hamza Issa (2022)  

Public Titre : Non-linear GNSS signal processing applied to land observation with high-rate airborne reflectometry Type de document : Thèse/HDR Auteurs : Hamza Issa, Auteur ; Serge Reboul, Directeur de thèse ; Ghaleb Faour, Directeur de thèse Editeur : Dunkerque : Université du Littoral-Côte-d'Opale Année de publication : 2022 Importance : 213 p. Format : 21 x 30 cm Note générale : Bibliographie Thèse en vue de l'obtention du grade de Docteur de l’Université du Littoral Côte d’Opale Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications [Termes IGN] bande L [Termes IGN] capteur aérien [Termes IGN] données radar [Termes IGN] humidité du sol [Termes IGN] modèle statistique [Termes IGN] précision métrique [Termes IGN] rapport signal sur bruit [Termes IGN] réflectométrie par GNSS [Termes IGN] signal GNSS [Termes IGN] zone humide Index. décimale : THESE Thèses et HDR Résumé : (Auteur) Soil moisture remote sensing has been an active area of research over the past few decades due to its essential role in agriculture and in the prediction of some natural disasters. GNSS-Reflectometry (GNSS-R) is an emerging bistatic remote sensing technique that uses the L-band GNSS signals as sources of opportunity to characterize Earth surface. In this passive radar system, the amplitudes of the GNSS signal reflected by soil and the GNSS signal received directly from the GNSS satellites can be used to derive measurements of reflectivity from which the soil moisture content of the surface is determined.The study of soil moisture content using reflectivity measurements can also be applied for the detection of in-land water body surfaces. In this dissertation, we propose in the first step a non-linear estimate of the GNSS signal amplitude. This estimate is based on a statistical model that we develop for the coherent detection of a GNSS signal quantized on 1 bit. We show with experimentations on synthetic and real data that the proposed estimator is more accurate than reference approaches and provide measurements of the Signal-to-Noise Ratio (SNR) at a higher rate. When the reflected GNSS signal is obtained in an airborne experiment, its evolution as a function of time is piecewise stationary. The different stationary parts are associatedto different kinds of reflecting surfaces. We propose in a second step a change point detector that takes into account the radar signal characteristics in order to segment the signal. We show on synthetic data that the proposed change point detector can detect and localize changes more accurately than reference approaches present in the literature. This work is applied to airborne GNSSR observation of Earth. We propose in the third step, a new GNSS-R sensor with its implementation on a lightweight airborne carrier. We also propose a new front-end receiver architecture, a software radio implementation of thereceiver, and the complete instrumentation of the airborne carrier. A real flight experimentation has taken place in the North of France obtaining reflections from different landforms. We show using the airborne GNSS measurements obtained, that the proposed radar technique detects different surfaces along the flight trajectory, and in particular in-land water bodies, with high temporal and spatial resolution. We also show that we can localize the edges of the detected water body surfaces at meter accuracy. Note de contenu : General Introduction 1. Remote Sensing of Soil Moisture 1.1 Introduction 1.2 L-band emissions of land covers 1.3 Soil moisture remote sensing techniques 1.4 Remote sensing using GNSS-R 1.5 Conclusion 2. Carrier-to-Noise Estimation : Application to Soil Moisture Retrieval using GNSS-R 2.1 Introduction 2.2 Signal and system model 2.3 C/N0 estimators 2.4 Soil moisture retrieval from GNSS-R 2.5 Conclusion 3. A Probabilistic Model for On-line Estimation of the GNSS Carrier?to-Noise Ratio 3.1 Introduction 3.2 1-bit coherent detection principle 3.3 GNSS front end 3.4 Estimation of the GNSS signal amplitude 3.5 Experimentation 3.6 Conclusion 4. Segmentation of the GNSS Signal Amplitudes 4.1 Introduction 4.2 Change point detection principle 4.3 On-line/Off-line change detection system 4.4 Experimentation 4.5 Conclusion 5. Airborne GNSS Reflectometry for Water Body Detection 5.1 Introduction 5.2 Airborne GNSS system 5.3 Airborne experimental setup 5.4 GNSS-R software receiver 5.5 Flight Experimentation 5.6 Data analysis 5.7 Conclusion General Conclusion Numéro de notice : 26837 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Thèse française Note de thèse : Thèse de Doctorat : Traitement du signal et des images : Université du Littoral Côte d’Opale : 2022 Organisme de stage : Laboratoire d'Informatique Signal et Image de la Côte d'Opale LISIC nature-HAL : Thèse DOI : sans Date de publication en ligne : 03/06/2022 En ligne : https://tel.archives-ouvertes.fr/tel-03687353/document Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101094

Python software to transform GPS SNR wave phases to volumetric water content / Angel Martín in GPS solutions, vol 26 n° 1 (January 2022)  

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Improving soil moisture retrieval from GNSS-interferometric reflectometry: parameters optimization and data fusion via neural network / Yajie Shi in International Journal of Remote Sensing IJRS, vol 42 n° 23 (1-10 December 2021)  

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Ten years of Lake Taupō surface height estimates using the GNSS interferometric reflectometry / Lucas D. Holden in Journal of geodesy, vol 95 n° 7 (July 2021)  

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SNR-based water height retrieval in rivers: Application to high amplitude asymmetric tides in the Garonne river / Pierre Zeiger in Remote sensing, vol 13 n° 9 (May-1 2021)  

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Python software tools for GNSS interferometric reflectometry (GNSS-IR) / Angel Martín in GPS solutions, Vol 24 n° 4 (October 2020)  

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Raytracing atmospheric delays in ground-based GNSS reflectometry / T. Nicolaidou in Journal of geodesy, vol 94 n° 8 (August 2020)  

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Real-time sea-level monitoring using Kalman filtering of GNSS-R data / Joakim Strandberg in GPS solutions, vol 23 n° 3 (July 2019)  

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Parameter estimation with GNSS-reflectometry and GNSS synthetic aperture techniques / Miguel Angel Ribot Sanfelix (2018)  

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Statistical comparison and combination of GPS, GLONASS, and multi-GNSS multipath reflectometry applied to snow depth retrieval / Sajad Tabibi in IEEE Transactions on geoscience and remote sensing, vol 55 n° 7 (July 2017)  

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Springer handbook of Global Navigation Satellite Systems / Peter J.G. Teunissen (2017)

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