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Temporal spectrum of spatial correlations between GNSS station position time series / Yujiao Niu in Journal of geodesy, vol 97 n° 2 (February 2023)  

Public [article]  inJournal of geodesy > vol 97 n° 2 (February 2023) . - n° 12 Titre : Temporal spectrum of spatial correlations between GNSS station position time series Type de document : Article/Communication Auteurs : Yujiao Niu, Auteur ; Paul Rebischung , Auteur ; Min Li, Auteur ; Na Wei, Auteur ; Chuang Shi, Auteur ; Zuheir Altamimi , Auteur Année de publication : 2023 Article en page(s) : n° 12 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] analyse spatio-temporelle [Termes IGN] bruit blanc [Termes IGN] corrélation automatique de points homologues [Termes IGN] filtrage du bruit [Termes IGN] série temporelle [Termes IGN] station GNSS [Termes IGN] transformation de Fourier [Vedettes matières IGN] Traitement de données GNSS Résumé : (auteur) The background noise in Global Navigation Satellite Systems (GNSS) station position time series is known to be both temporally and spatially correlated. Its temporal correlations are well modeled and routinely taken into account when deriving parameters of interest like station velocities. On the other hand, a general model of the spatial correlations in GNSS time series is lacking, and they are usually ignored, although their consideration could benefit several purposes such as offset detection, velocity estimation or spatial filtering. In order to improve the realism of current spatio-temporal correlation models, we investigate in this study how the spatial correlations of GNSS time series vary with the temporal frequency. A frequency-dependent measure of the spatial correlations is therefore introduced and applied to station position time series from the latest reprocessing campaign of the International GNSS Service (IGS), as well as to Precise Point Positioning time series provided by the Nevada Geodetic Laboratory (NGL). Different spatial correlation regimes are thus evidenced at different temporal frequencies. The different levels of spatial correlations between IGS and NGL datasets furthermore suggest that some part of the spatially correlated background noise in GNSS time series consists of GNSS errors rather than aperiodic Earth surface deformation signal. Numéro de notice : A2025-145 Affiliation des auteurs : UMR IPGP-Géod+Ext (2020- ) Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s00190-023-01703-7 Date de publication en ligne : 06/02/2023 En ligne : https://doi.org/10.1007/s00190-023-01703-7 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102746 [article]

Impact of offsets on assessing the low-frequency stochastic properties of geodetic time series / Kevin Gobron in Journal of geodesy, vol 96 n° 7 (July 2022)  

Public [article]  inJournal of geodesy > vol 96 n° 7 (July 2022) . - n° 46 Titre : Impact of offsets on assessing the low-frequency stochastic properties of geodetic time series Type de document : Article/Communication Auteurs : Kevin Gobron, Auteur ; Paul Rebischung , Auteur ; Olivier de Viron, Auteur ; Alain Demoulin, Auteur ; Michel Van Camp, Auteur Année de publication : 2022 Projets : 3-projet - voir note / Article en page(s) : n° 46 Note générale : bibliographie This study has been financially supported by the Direction Générale de l’Armement (DGA), the Nouvelle-Aquitaine region, and the Centre National des Etudes Spatiales (CNES) as an application of the geodesy missions. This research was also supported by the Brain LASUGEO project entitled “monitoring LAnd SUbsidence caused by Groundwater exploitation through gEOdetic measurements” funded by the Belgian Sciences Policy. Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géodésie spatiale [Termes IGN] analyse de variance [Termes IGN] bruit blanc [Termes IGN] fréquence [Termes IGN] méthode du maximum de vraisemblance (estimation) [Termes IGN] modèle de Gauss-Markov [Termes IGN] modèle stochastique [Termes IGN] série temporelle [Termes IGN] vitesse Résumé : (auteur) Understanding and modelling the properties of the stochastic variations in geodetic time series is crucial to obtain realistic uncertainties for deterministic parameters, e.g., long-term velocities, and helpful in characterizing non-modelled processes. With the increasing span of geodetic time series, it is expected that additional observations would help better understand the low-frequency properties of these stochastic variations. In the meantime, recent studies evidenced that the choice of the functional model for the time series biases the assessment of these low-frequency stochastic properties. In particular, frequent offsets in position time series can hinder the evaluation of the noise level at low frequencies and prevent the detection of possible random-walk-type variability. This study investigates the ability of the Maximum Likelihood Estimation (MLE) method to correctly retrieve low-frequency stochastic properties of geodetic time series in the presence of frequent offsets. We show that part of the influence of offsets reported by previous studies results from the MLE method estimation biases. These biases occur even when all offset epochs are correctly identified and accounted for in the trajectory model. They can cause a dramatic underestimation of deterministic parameter uncertainties. We show that one can avoid biases using the Restricted Maximum Likelihood Estimation (RMLE) method. Yet, even when using the RMLE method or equivalent, adding offsets to the trajectory model inevitably blurs the estimated low-frequency properties of geodetic time series by increasing low-frequency stochastic parameter uncertainties more than other stochastic parameters. Numéro de notice : A2022-519 Affiliation des auteurs : UMR IPGP-Géod+Ext (2020- ) Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s00190-022-01634-9 Date de publication en ligne : 29/06/2022 En ligne : https://doi.org/10.1007/s00190-022-01634-9 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101072 [article]

Effect of label noise in semantic segmentation of high resolution aerial images and height data / Arabinda Maiti in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol V-2-2022 (2022 edition)  

Public [article]  inISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences > vol V-2-2022 (2022 edition) . - pp 275 - 282 Titre : Effect of label noise in semantic segmentation of high resolution aerial images and height data Type de document : Article/Communication Auteurs : Arabinda Maiti, Auteur ; Sander J. Oude Elberink, Auteur ; M. George Vosselman, Auteur Année de publication : 2022 Article en page(s) : pp 275 - 282 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] apprentissage profond [Termes IGN] bruit (théorie du signal) [Termes IGN] données altimétriques [Termes IGN] données d'entrainement (apprentissage automatique) [Termes IGN] image à très haute résolution [Termes IGN] image aérienne [Termes IGN] orthoimage [Termes IGN] segmentation sémantique Résumé : (auteur) The performance of deep learning models in semantic segmentation is dependent on the availability of a large amount of labeled data. However, the influence of label noise, in the form of incorrect annotations, on the performance is significant and mostly ignored. This is a big concern in remote sensing applications, wherein acquired datasets are spatially limited, labeling is done by domain experts with possible sources of high inter-and intra-observer variability leading to erroneous predictions. In this paper, we first simulate the label noise while conducting experiments on two different datasets with very high-resolution aerial images, height data, and inaccurate labels, responsible for the training of deep learning models. We then focus on the effect of these noises on the model performance. Different classes respond differently to the label noise. The typical size of an object belonging to a class is a crucial factor regarding the class-specific performance of the model trained with erroneous labels. Errors caused by relative shifts of labels are the most influential label errors. The model is generally more tolerant of the random label noise than other label errors. It has been observed that the accuracy gets reduced by at least 3% while 5% of label pixels are erroneous. In this regard, our study provides a new perspective of evaluating and quantifying the propagation of label noise in the model performance that is indeed important for adopting reliable semantic segmentation practices. Numéro de notice : A2022-434 Affiliation des auteurs : non IGN Thématique : IMAGERIE/INFORMATIQUE Nature : Article DOI : 10.5194/isprs-annals-V-2-2022-275-2022 Date de publication en ligne : 17/05/2022 En ligne : https://doi.org/10.5194/isprs-annals-V-2-2022-275-2022 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100741 [article]

Results on GNSS spoofing mitigation using multiple receivers / Niklas Stenberg in Navigation : journal of the Institute of navigation, vol 69 n° 1 (Spring 2022)  

Public [article]  inNavigation : journal of the Institute of navigation > vol 69 n° 1 (Spring 2022) . - n° 510 Titre : Results on GNSS spoofing mitigation using multiple receivers Type de document : Article/Communication Auteurs : Niklas Stenberg, Auteur ; Erik Axell, Auteur ; Jouni Rantakokko, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 510 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement du signal [Termes IGN] atténuation du signal [Termes IGN] bruit (théorie du signal) [Termes IGN] détection de leurrage [Termes IGN] détection du signal [Termes IGN] double différence [Termes IGN] erreur de phase [Termes IGN] leurrage [Termes IGN] mesurage de pseudo-distance [Termes IGN] récepteur GNSS Résumé : (auteur) GNSS receivers are vulnerable to spoofing attacks in which false satellite signals deceive receivers to compute false position and/or time estimates. This work derives and evaluates algorithms that perform spoofing mitigation by utilizing double differences of pseudorange or carrier phase measurements from multiple receivers. The algorithms identify pseudorange and carrier-phase measurements originating from spoofing signals, and omit these from the position and time computation. The algorithms are evaluated with simulated and live-sky meaconing attacks. The simulated spoofing attacks show that mitigation using pseudoranges is possible in these tests when the receivers are separated by five meters or more. At 20 meters, the pseudorange algorithm correctly authenticates six out of seven pseudoranges within 30 seconds in the same simulator tests. Using carrier phase allows mitigation with shorter distances between receivers, but requires better time synchronization between the receivers. Evaluations with live-sky meaconing attacks show the validity of the proposed mitigation algorithms. Numéro de notice : A2022-821 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article DOI : 10.33012/navi.510 En ligne : https://doi.org/10.33012/navi.510 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101989 [article]

Multi-frequency quadrifilar helix antennas for cm-accurate GNSS positioning / Lambert Wanninger in Journal of applied geodesy, vol 16 n° 1 (January 2022)  

Public [article]  inJournal of applied geodesy > vol 16 n° 1 (January 2022) . - pp 25 - 35 Titre : Multi-frequency quadrifilar helix antennas for cm-accurate GNSS positioning Type de document : Article/Communication Auteurs : Lambert Wanninger, Auteur ; Melanie Thiemig, Auteur ; Walker Frevert, Auteur Année de publication : 2022 Article en page(s) : pp 25 - 35 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géodésie spatiale [Termes IGN] antenne GNSS [Termes IGN] bruit (théorie du signal) [Termes IGN] étalonnage d'instrument [Termes IGN] fréquence multiple [Termes IGN] phase GNSS [Termes IGN] positionnement par GNSS [Termes IGN] précision centimétrique [Termes IGN] signal GNSS [Termes IGN] trajet multiple Résumé : (auteur) For a few years now, GNSS multi-frequency quadrifilar helix antennas (QHA) are available to be used for precise GNSS applications. We performed test measurements with two types of multi-frequency QHA and compared them with a geodetic patch antenna. Although code and carrier phase noise and high-frequent multipath was determined to be larger as compared to the geodetic antenna, the fast-static horizontal coordinate accuracies are on the same level and demonstrate cm-accuracy capability. One of the QHA types exhibited an increased susceptibility to near-field multipath effects which resulted in a degraded accuracy of the vertical coordinate component. Numéro de notice : A2022-054 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article DOI : 10.1515/jag-2021-0042 Date de publication en ligne : 15/09/2021 En ligne : https://doi.org/10.1515/jag-2021-0042 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99449 [article]

A multipath and thermal noise joint error characterization and exploitation for low-cost GNSS PVT estimators in urban environment / Eustachio Roberto Matera (2022)  

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Deep learning-based image de-raining using discrete Fourier transformation / Prasen Kumar Sharma in The Visual Computer, vol 37 n° 8 (August 2021)  

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Impact of the third frequency GNSS pseudorange and carrier phase observations on rapid PPP convergences / Jiang Guo in GPS solutions, vol 25 n° 2 (April 2021)  

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Cluster-based empirical tropospheric corrections applied to InSAR time series analysis / Kyle Dennis Murray in IEEE Transactions on geoscience and remote sensing, Vol 59 n° 3 (March 2021)  

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Denoising Sentinel-1 extra-wide mode cross-polarization images over sea ice / Yan Sun in IEEE Transactions on geoscience and remote sensing, Vol 59 n° 3 (March 2021)  

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G-band radar for humidity and cloud remote sensing / Ken B. Cooper in IEEE Transactions on geoscience and remote sensing, vol 59 n° 2 (February 2021)  

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Improving trajectory estimation using 3D city models and kinematic point clouds / Lucas Lucks in Transactions in GIS, Vol 25 n° 1 (February 2021)  

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Applied signal processing / Sadasivan Puthusserypady (2021)  

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Characteristics of seasonal variations and noises of the daily double-difference and PPP solutions / Kamil Maciuk in Journal of applied geodesy, vol 15 n° 1 (January 2021)  

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GNSS/5G Hybridization for Urban Navigation / Anne-Marie Tobie (2021)  

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