Survey review . vol 55 n° 388Paru le : 01/01/2023 |
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Ajouter le résultat dans votre panierComparative analysis of real-time precise point positioning method in terms of positioning and zenith tropospheric delay estimation / Omer Faruk Atiz in Survey review, vol 55 n° 388 (January 2023)
[article]
Titre : Comparative analysis of real-time precise point positioning method in terms of positioning and zenith tropospheric delay estimation Type de document : Article/Communication Auteurs : Omer Faruk Atiz, Auteur ; Salih Alcay, Auteur ; Sermet Ogutcu, Auteur ; Ilkay Bugdayci, Auteur Année de publication : 2022 Article en page(s) : pp Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Navigation et positionnement
[Termes IGN] analyse comparative
[Termes IGN] positionnement ponctuel précis
[Termes IGN] retard troposphérique zénithal
[Termes IGN] RTKLIB
[Termes IGN] temps réelRésumé : (auteur) The positioning performance of widely used real-time precise point positioning (RT-PPP) software packages BNC, RTKLIB, and PPP-WIZARD were tested in terms of convergence time and accuracy. The convergence time of PPP-WIZARD solutions is reduced by ambiguity resolution (AR). The GPS + GLONASS + GALILEO (GRE) mode improved the convergence time of GPS + GALILEO (GE) mode by 22.0%, 15.5%, 17.1%, and 11.4% for the BNC, RTKLIB, PPP-WIZARD (AR) and PPP-WIZARD, respectively. For the GRE mode, RMSEs of the BNC, RTKLIB, PPP-WIZARD (AR), and PPP-WIZARD software packages in the horizontal/vertical component are 3.8/5.6, 2.6/6.2, 3.3/6.5, 4.3/7.0 cm, respectively. In comparison with the IGS-ZTD (International GNSS Service ZTD), BNC, RTKLIB, PPP-WIZARD (AR), and PPP-WIZARD solutions show a mean bias of 0.28, −0.72, 2.80, and 2.83 cm, respectively in GE mode. The GRE mode reduced the RMSEs of the ZTD estimations of BNC, RTKLIB, PPP-WIZARD (AR) and PPP-WIZARD by 2.9%, 5.1%, 0.6%, and 0.4% respectively. Numéro de notice : A2022-014 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article DOI : 10.1080/00396265.2021.2001627 Date de publication en ligne : 22/11/2021 En ligne : https://doi.org/10.1080/00396265.2021.2001627 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99089
in Survey review > vol 55 n° 388 (January 2023) . - pp[article]Filtering airborne LIDAR data by using fully convolutional networks / Abdullah Varlik in Survey review, vol 55 n° 388 (January 2023)
[article]
Titre : Filtering airborne LIDAR data by using fully convolutional networks Type de document : Article/Communication Auteurs : Abdullah Varlik, Auteur ; Firat Uray, Auteur Année de publication : 2022 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] classification par réseau neuronal convolutif
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] filtrage de points
[Termes IGN] segmentation
[Termes IGN] semis de pointsRésumé : (auteur) The classification of LIDAR point clouds has always been a challenging task. Classification refers to label each point in different categories, such as ground, vegetation or building. The success of deep learning techniques in image processing tasks have encouraged researchers to use deep neural networks for classification of LIDAR point clouds. In this paper, we proposed a U-Net based architecture capable of classifying LIDAR data. The results indicated that our network model achieved an average F1 score of 91% over all three classes (ground, vegetation and building) for our best model. Numéro de notice : A2022-015 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1080/00396265.2021.1996798 Date de publication en ligne : 11/11/2021 En ligne : https://doi.org/10.1080/00396265.2021.1996798 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99093
in Survey review > vol 55 n° 388 (January 2023)[article]Positioning performance of GNSS-PPP and PPP-AR methods for determining the vertical displacements / Burak Akpinar in Survey review, vol 55 n° 388 (January 2023)
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Titre : Positioning performance of GNSS-PPP and PPP-AR methods for determining the vertical displacements Type de document : Article/Communication Auteurs : Burak Akpinar, Auteur Année de publication : 2022 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Navigation et positionnement
[Termes IGN] analyse comparative
[Termes IGN] ouvrage d'art
[Termes IGN] positionnement par GNSS
[Termes IGN] positionnement ponctuel précis
[Termes IGN] précision millimétrique
[Termes IGN] résolution d'ambiguïté
[Termes IGN] surveillance d'ouvrageRésumé : (auteur) This study investigates the accuracy of vertical displacements monitored by Global Navigation Satellite Systems (GNSS) precise point positioning (PPP) with float-ambiguity solution and with ambiguity resolution (PPP-AR). For this purpose, a simulation was designed. The static GNSS observations were collected at a test point during different observation times over seven periods involving vertical displacements produced with a precision of less than one mm. Each set of GNSS observations was processed with both GNSS-PPP and PPP-AR methods. The results revealed that RMS values of PPP-AR solutions are about twice better than RMS values of PPP solution for all observation times and all vertical displacement values. Numéro de notice : A2022-033 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article DOI : 10.1080/00396265.2021.2010018 Date de publication en ligne : 13/12/2021 En ligne : https://doi.org/10.1080/00396265.2021.2010018 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99295
in Survey review > vol 55 n° 388 (January 2023)[article]