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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]

Multi-GNSS phase delay estimation and PPP ambiguity resolution : GPS, BDS, GLONASS, Galileo / Xingxing Li in Journal of geodesy, vol 92 n° 6 (June 2018)  

Public [article]  inJournal of geodesy > vol 92 n° 6 (June 2018) . - pp 579 – 608 Titre : Multi-GNSS phase delay estimation and PPP ambiguity resolution : GPS, BDS, GLONASS, Galileo Type de document : Article/Communication Auteurs : Xingxing Li, Auteur ; Xin Li, Auteur ; Yongqiang Yuan, Auteur ; Keke Zhang, Auteur ; Xiaohong Zhang, Auteur ; Jens Wickert, Auteur Année de publication : 2018 Article en page(s) : pp 579 – 608 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géodésie spatiale [Termes IGN] ambiguïté entière [Termes IGN] délai d'obtention de la première position [Termes IGN] positionnement par BeiDou [Termes IGN] positionnement par Galileo [Termes IGN] positionnement par GLONASS [Termes IGN] positionnement par GNSS [Termes IGN] positionnement par GPS [Termes IGN] positionnement ponctuel précis [Termes IGN] résolution d'ambiguïté Résumé : (Auteur) This paper focuses on the precise point positioning (PPP) ambiguity resolution (AR) using the observations acquired from four systems: GPS, BDS, GLONASS, and Galileo (GCRE). A GCRE four-system uncalibrated phase delay (UPD) estimation model and multi-GNSS undifferenced PPP AR method were developed in order to utilize the observations from all systems. For UPD estimation, the GCRE-combined PPP solutions of the globally distributed MGEX and IGS stations are performed to obtain four-system float ambiguities and then UPDs of GCRE satellites can be precisely estimated from these ambiguities. The quality of UPD products in terms of temporal stability and residual distributions is investigated for GPS, BDS, GLONASS, and Galileo satellites, respectively. The BDS satellite-induced code biases were corrected for GEO, IGSO, and MEO satellites before the UPD estimation. The UPD results of global and regional networks were also evaluated for Galileo and BDS, respectively. As a result of the frequency-division multiple-access strategy of GLONASS, the UPD estimation was performed using a network of homogeneous receivers including three commonly used GNSS receivers (TRIMBLE NETR9, JAVAD TRE_G3TH DELTA, and LEICA). Data recorded from 140 MGEX and IGS stations for a 30-day period in January in 2017 were used to validate the proposed GCRE UPD estimation and multi-GNSS dual-frequency PPP AR. Our results show that GCRE four-system PPP AR enables the fastest time to first fix (TTFF) solutions and the highest accuracy for all three coordinate components compared to the single and dual system. An average TTFF of 9.21 min with 7∘ cutoff elevation angle can be achieved for GCRE PPP AR, which is much shorter than that of GPS (18.07 min), GR (12.10 min), GE (15.36 min) and GC (13.21 min). With observations length of 10 min, the positioning accuracy of the GCRE fixed solution is 1.84, 1.11, and 1.53 cm, while the GPS-only result is 2.25, 1.29, and 9.73 cm for the east, north, and vertical components, respectively. When the cutoff elevation angle is increased to 30∘, the GPS-only PPP AR results are very unreliable, while 13.44 min of TTFF is still achievable for GCRE four-system solutions. Numéro de notice : A2018-153 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s00190-017-1081-3 Date de publication en ligne : 31/10/2017 En ligne : https://doi.org/10.1007/s00190-017-1081-3 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=89766 [article]

Multi-technique comparison of atmospheric parameters at the DORIS co-location sites during CONT14 / Robert Heinkelmann in Advances in space research, vol 58 n° 12 (15 December 2016)  

Public [article]  inAdvances in space research > vol 58 n° 12 (15 December 2016) . - pp 2758 - 2773 Titre : Multi-technique comparison of atmospheric parameters at the DORIS co-location sites during CONT14 Type de document : Article/Communication Auteurs : Robert Heinkelmann, Auteur ; Pascal Willis , Auteur ; Zhiguo Deng, Auteur ; Galina Dick, Auteur ; Tobias Nilsson, Auteur ; Benedikt Soja, Auteur ; Florian Zus, Auteur ; Jens Wickert, Auteur ; Harald Schuh, Auteur Année de publication : 2016 Article en page(s) : pp 2758 - 2773 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Systèmes de référence et réseaux [Termes IGN] analyse comparative [Termes IGN] antenne DORIS [Termes IGN] co-positionnement [Termes IGN] modèle météorologique [Termes IGN] retard troposphérique zénithal [Termes IGN] station permanente Résumé : (auteur) The atmospheric parameters, zenith delays and gradients, obtained by the DORIS, GPS, VLBI, and numerical weather models, ECMWF and NCEP, are compared at five DORIS co-located sites during the 15 days of the CONT14 campaign from 2014-05-06 until 2014-05-20. Further examined are two different solutions of GPS, VLBI and NCEP: for GPS, a network solution comparable to the TIGA reprocessing analysis strategy and a precise point positioning solution, for VLBI, a least squares and a Kalman filtered and smoothed solution, and for NCEP two spatial resolutions, 0.5° and 1.0°, are tested. The different positions of the antenna reference points at co-location sites affect the atmospheric parameters and have to be considered prior to the comparison. We assess and discuss these differences, tropospheric ties, by comparing ray-traced atmospheric parameters obtained at the positions of the various antenna reference points. While ray-traced ZHD and ZWD at the co-located antennas significantly differ, the ray-traced gradients show only very small differences. Weather events can introduce larger disagreement between atmospheric parameters obtained at co-location sites. The various weather model solutions in general agree very well in providing tropospheric ties. The atmospheric parameters are compared using statistical methods, such as the mean difference and standard deviations with repect to a weighted mean value. While GPS and VLBI atmospheric parameters agree very well in general, the DORIS observations are in several cases not dense enough to achieve a comparable level of agreement. The estimated zenith delays from DORIS, however, are competitive with the other space geodetic techniques. If the DORIS observation geometry is insufficient for the estimation of an atmospheric gradient, less than three satellites observed during the definition interval, the DORIS atmospheric parameters degrade and show small quasi-periodic variations that correlate with the number of observations and in particular with the number of satellites. An increase in the DORIS constellation concerning more satellites and in general more observations is very likely to significantly improve the quality of DORIS derived atmospheric parameters. For the first time, we tested a 6 h sampling of the DORIS gradients. Where the observations are sufficiently dense, the increased sampling results in an improvement of the agreement of the DORIS gradients with the other solutions. Numéro de notice : A2016--184 Affiliation des auteurs : LASTIG LAREG+Ext (2012-mi2018) Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.asr.2016.09.023 Date de publication en ligne : 29/09/2016 En ligne : https://doi.org/10.1016/j.asr.2016.09.023 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=91819 [article]

Long-term soil moisture dynamics derived from GNSS interferometric reflectometry: a case study for Sutherland, South Africa / Sibylle Vey in GPS solutions, vol 20 n° 4 (October 2016)  

Public [article]  inGPS solutions > vol 20 n° 4 (October 2016) . - pp 641 - 654 Titre : Long-term soil moisture dynamics derived from GNSS interferometric reflectometry: a case study for Sutherland, South Africa Type de document : Article/Communication Auteurs : Sibylle Vey, Auteur ; Jens Wickert, Auteur Année de publication : 2016 Article en page(s) : pp 641 - 654 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de géodésie spatiale [Termes IGN] Afrique du sud (état) [Termes IGN] analyse diachronique [Termes IGN] humidité du sol [Termes IGN] rapport signal sur bruit [Termes IGN] récepteur GNSS [Termes IGN] réflectométrie par GNSS [Termes IGN] signal GNSS [Termes IGN] variation temporelle Résumé : (Auteur) Soil moisture is a geophysical key observable for predicting floods and droughts, modeling weather and climate and optimizing agricultural management. Currently available in situ observations are limited to small sampling volumes and restricted number of sites, whereas measurements from satellites lack spatial resolution. Global navigation satellite system (GNSS) receivers can be used to estimate soil moisture time series at an intermediate scale of about 1000 m2. In this study, GNSS signal-to-noise ratio (SNR) data at the station Sutherland, South Africa, are used to estimate soil moisture variations during 2008–2014. The results capture the wetting and drying cycles in response to rainfall. The GNSS Volumetric Water Content (VWC) is highly correlated (r2 = 0.8) with in situ observations by time-domain reflectometry sensors and is accurate to 0.05 m3/m3. The soil moisture estimates derived from the SNR of the L1 and L2P signals compared to the L2C show small differences with a RMSE of 0.03 m3/m3. A reduction in the SNR sampling rate from 1 to 30 s has very little impact on the accuracy of the soil moisture estimates (RMSE of the VWC difference 1–30 s is 0.01 m3/m3). The results show that the existing data of the global tracking network with continuous observations of the L1 and L2P signals with a 30-s sampling rate over the last two decades can provide valuable complementary soil moisture observations worldwide. Numéro de notice : A2016--026 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article DOI : 10.1007/s10291-015-0474-0 En ligne : http://dx.doi.org/10.1007/s10291-015-0474-0 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=83927 [article]