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An assessment of wide-lane ambiguity resolution methods for multi-frequency multi-GNSS precise point positioning / Viet Duong in Survey review, vol 52 n° 374 (August 2020)
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Titre : An assessment of wide-lane ambiguity resolution methods for multi-frequency multi-GNSS precise point positioning Type de document : Article/Communication Auteurs : Viet Duong, Auteur ; Ken Harima, Auteur ; Suelynn Choy, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 442 - 453 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géodésie spatiale
[Termes descripteurs IGN] combinaison linéaire
[Termes descripteurs IGN] délai d'obtention de la première position
[Termes descripteurs IGN] fréquence multiple
[Termes descripteurs IGN] mesurage de phase
[Termes descripteurs IGN] mesurage par GNSS
[Termes descripteurs IGN] phase
[Termes descripteurs IGN] positionnement par GNSS
[Termes descripteurs IGN] positionnement ponctuel précis
[Termes descripteurs IGN] résolution d'ambiguïté
[Termes descripteurs IGN] station GNSS
[Termes descripteurs IGN] taux d'échantillonnageRésumé : (auteur) We assess the time-to-first-fix (TTFF) and the ambiguity fixing rate of two PPP wide-lane ambiguity resolution (WL-AR) methods, namely the geometry-based and ionospheric-free (GB-IF) method, and the geometry-free and ionospheric-free (GF-IF) method. First, an optimal GF-IF WL linear combination is selected based on the ratio between the code and carrier phase measurement noise (RT). Then, the relation between ambiguity variance and satellite geometry in the GB-IF WL-AR is investigated. Both simulated and real data from 31 GNSS stations over 37 consecutive days in 2017 were used. Numerical results show that the GF-IF WL-AR method has shorter TTFF and higher ambiguity fixing rate compared to the GB-IF method when RT≤150. However, when RT≥150, the GB-IF method outperforms the GF-IF method. Depending on RT values used, 2–10 min would be required to resolve the WL ambiguities when using GNSS measurements with one second sampling rate. Numéro de notice : A2020-518 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/00396265.2019.1634339 date de publication en ligne : 02/07/2019 En ligne : https://doi.org/10.1080/00396265.2019.1634339 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95678
in Survey review > vol 52 n° 374 (August 2020) . - pp 442 - 453[article]Precise point positioning with decimetre accuracy using wide-lane ambiguities and triple-frequency GNSS data / Manoj Deo in Journal of applied geodesy, vol 14 n° 3 (July 2020)
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Titre : Precise point positioning with decimetre accuracy using wide-lane ambiguities and triple-frequency GNSS data Type de document : Article/Communication Auteurs : Manoj Deo, Auteur ; Ahmed El-Mowafy, Auteur Année de publication : 2020 Article en page(s) : pp 263 – 284 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Navigation et positionnement
[Termes descripteurs IGN] ambiguïté entière
[Termes descripteurs IGN] bruit atmosphérique
[Termes descripteurs IGN] combinaison linéaire
[Termes descripteurs IGN] données GNSS
[Termes descripteurs IGN] phase
[Termes descripteurs IGN] positionnement ponctuel précis
[Termes descripteurs IGN] triple différenceRésumé : (auteur) This paper proposes precise point positioning (PPP) methods that offer an accuracy of a few decimetres (dm) with triple frequency GNSS data. Firstly, an enhanced triple frequency linear combination is presented for rapid fixing of the extra wide-lane (EWL) and wide-lane (WL) ambiguities for GPS, Beidou-2 and Galileo. This has improved performance compared to the Melbourne-Wübbena (MW) linear combination, and has 6.7 % lower measurement noise for the GPS L1/L2 signals, 12.7 % for L1/L5 and 0.7 % for L2/L5. Analysis with tested data showed a 5–6 % reduction in time required to fix the N21 and N51 ambiguities. Once the EWL/WL ambiguities are fixed with the proposed linear combinations, three methods are presented that aim to provide positioning accuracy of a few dm. In the first approach, the three EWL/WL ambiguities in their respective phase equations are used to derive a low-noise ionosphere-free (IF) linear combination. The second method uses a low noise IF combination with two carrier-phase EWL/WL equations and a single pseudorange measurement. The third method uses a low noise IF combination with a single carrier phase EWL equation and two pseudorange measurements. These proposed methods can provide dm level positioning accuracy if carrier phase measurements with mm precision is tracked by the receiver. When comparing these combinations with a combination proposed in [], it is found that superior performance is achieved with the third method when carrier phase noise is >5–6 mm for GPS and Beidou-2 and >2–3 mm for Galileo. This model only requires the EWL ambiguity to be fixed which typically takes just one epoch of data. Thus, the user achieves instant decimetre level PPP accuracy. Numéro de notice : A2020-466 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1515/jag-2019-0068 date de publication en ligne : 11/03/2020 En ligne : https://doi.org/10.1515/jag-2019-0068 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95432
in Journal of applied geodesy > vol 14 n° 3 (July 2020) . - pp 263 – 284[article]Predicting displacement of bridge based on CEEMDAN-KELM model using GNSS monitoring data / Qian Fan in Journal of applied geodesy, vol 14 n° 3 (July 2020)
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Titre : Predicting displacement of bridge based on CEEMDAN-KELM model using GNSS monitoring data Type de document : Article/Communication Auteurs : Qian Fan, Auteur ; Xiaolin Meng, Auteur ; Dinh Tung Nguyen, Auteur ; Yilin Xie, Auteur ; Jiayong Yu, Auteur Année de publication : 2020 Article en page(s) : pp 253 – 261 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Topographie moderne
[Termes descripteurs IGN] apprentissage automatique
[Termes descripteurs IGN] combinaison linéaire
[Termes descripteurs IGN] données GNSS
[Termes descripteurs IGN] méthode fondée sur le noyau
[Termes descripteurs IGN] pont
[Termes descripteurs IGN] prévention des risques
[Termes descripteurs IGN] série temporelle
[Termes descripteurs IGN] surveillance d'ouvrageRésumé : (auteur) Bridges are critical to economic and social development of a country. In order to ensure the safe operation of bridges, it is of great significance to accurately predict displacement of monitoring points from bridge Structural Health System (SHM). In the paper, a CEEMDAN-KELM model is proposed to improve the accuracy of displacement prediction of bridge. Firstly, the original displacement monitoring time series of bridge is accurately and effectively decomposed into multiple components called intrinsic mode functions (IMFs) and one residual component using a method named complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN). Then, these components are forecasted by establishing appropriate kernel extreme learning machine (KELM) prediction models, respectively. At last, the prediction results of all components including residual component are summed as the final prediction results. A case study using global navigation satellite system (GNSS) monitoring data is used to illustrate the feasibility and validity of the proposed model. Practical results show that prediction accuracy using CEEMDAN-KELM model is superior to BP neural network model, EMD-ELM model and EMD-KELM model in terms of the same monitoring data. Numéro de notice : A2020-396 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1515/jag-2019-0057 date de publication en ligne : 27/03/2020 En ligne : https://doi.org/10.1515/jag-2019-0057 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95431
in Journal of applied geodesy > vol 14 n° 3 (July 2020) . - pp 253 – 261[article]Carrier phase bias estimation of geometry-free linear combination of GNSS signals for ionospheric TEC modeling / Anna Krypiak-Gregorczyk in GPS solutions, vol 22 n° 2 (April 2018)
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Titre : Carrier phase bias estimation of geometry-free linear combination of GNSS signals for ionospheric TEC modeling Type de document : Article/Communication Auteurs : Anna Krypiak-Gregorczyk, Auteur ; Pawel Wielgosz, Auteur Année de publication : 2018 Article en page(s) : pp 22 - 45 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Termes descripteurs IGN] combinaison linéaire
[Termes descripteurs IGN] erreur systématique
[Termes descripteurs IGN] modèle ionosphérique
[Termes descripteurs IGN] phase
[Termes descripteurs IGN] positionnement par GNSS
[Termes descripteurs IGN] retard ionosphèrique
[Termes descripteurs IGN] signal GNSS
[Termes descripteurs IGN] teneur totale en électrons
[Vedettes matières IGN] Traitement de données GNSSRésumé : (Auteur) The ionosphere can be modeled and studied using multi-frequency GNSS signals and their geometry-free linear combination. Therefore, a number of GNSS-derived ionospheric models have been developed and applied in a broad range of applications. However, due to the complexity of estimating the carrier phase ambiguities, most of these models are based on low-accuracy carrier phase smoothed pseudorange data. This, in turn, critically limits their accuracy and applicability. Therefore, we present a new methodology of estimating the phase bias of the scaled L1 and L2 carrier phase difference which is a function of the ambiguities, the ionospheric delay, and hardware delays. This methodology is suitable for ionospheric modeling at regional and continental scales. In addition, we present its evaluation under varying ionospheric conditions. The test results show that the carrier phase bias of geometry-free linear combination can be estimated with a very high accuracy, which consequently allows for calculating ionospheric TEC with the uncertainty lower than 1.0 TECU. This high accuracy makes the resulting ionosphere model suitable for improving GNSS positioning for high-precision applications in geosciences. Numéro de notice : A2018-160 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s10291-018-0711-4 date de publication en ligne : 16/02/2018 En ligne : https://doi.org/10.1007/s10291-018-0711-4 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=89783
in GPS solutions > vol 22 n° 2 (April 2018) . - pp 22 - 45[article]From subpixel to superpixel : a novel fusion framework for hyperspectral image classification / Ting Lu in IEEE Transactions on geoscience and remote sensing, vol 55 n° 8 (August 2017)
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Titre : From subpixel to superpixel : a novel fusion framework for hyperspectral image classification Type de document : Article/Communication Auteurs : Ting Lu, Auteur ; Shutao Li, Auteur ; Leyuan Fang, Auteur ; et al., Auteur Année de publication : 2017 Article en page(s) : pp 4398 - 4411 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes descripteurs IGN] analyse des mélanges spectraux
[Termes descripteurs IGN] analyse infrapixellaire
[Termes descripteurs IGN] classification par séparateurs à vaste marge
[Termes descripteurs IGN] classification pixellaire
[Termes descripteurs IGN] combinaison linéaire
[Termes descripteurs IGN] fusion d'images
[Termes descripteurs IGN] image hyperspectrale
[Termes descripteurs IGN] méthode fondée sur le noyauRésumé : (Auteur) Supervised classification of hyperspectral images (HSI) is a very challenging task due to the existence of noisy and mixed spectral characteristics. Recently, the widely developed spectral unmixing techniques offer the possibility to extract spectral mixture information at a subpixel level, which can contribute to the categorization of seriously mixed spectral pixels. Besides, it has been demonstrated that the discrimination between different materials will be improved by integrating the geometry and structure information, which can be derived from the variance between neighboring pixels. Furthermore, by incorporating the spatial context, the superpixel-based spectral-spatial similarity information can be used to smooth classification results in homogeneous regions. Therefore, a novel fusion framework for HSI classification that combines subpixel, pixel, and superpixel-based complementary information is proposed in this paper. Here, both feature fusion and decision fusion schemes are introduced. For the feature fusion scheme, the first step is to extract subpixel-level, pixel-level, and superpixel-level features from HSI, respectively. Then, the multiple feature-induced kernels are fused to form one composite kernel, which is incorporated with a support vector machine (SVM) classifier for label assignment. For the decision fusion scheme, class probabilities based on three different features are estimated by the probabilistic SVM classifier first. Then, the class probabilities are adaptively fused to form a probabilistic decision rule for classification. Experimental results tested on different real HSI images can demonstrate the effectiveness of the proposed fusion schemes in improving discrimination capability, when compared with the classification results relied on each individual feature. Numéro de notice : A2017-654 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2017.2691906 En ligne : http://dx.doi.org/10.1109/TGRS.2017.2691906 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=86439
in IEEE Transactions on geoscience and remote sensing > vol 55 n° 8 (August 2017) . - pp 4398 - 4411[article]A novel preunmixing framework for efficient detection of linear mixtures in hyperspectral images / Andrea Marinoni in IEEE Transactions on geoscience and remote sensing, vol 55 n° 8 (August 2017)
PermalinkNew optimal smoothing scheme for improving relative and absolute accuracy of tightly coupled GNSS/SINS integration / Xiaohong Zhang in GPS solutions, vol 21 n° 3 (July 2017)
PermalinkAn improved between-satellite single-difference precise point positioning model for combined GPS/Galileo observations / Akram Afifi in Journal of applied geodesy, vol 9 n° 2 (June 2015)
PermalinkAmbiguity resolution for triple-frequency geometry-free and ionosphere-free combination tested with real data / K. Wang in Journal of geodesy, vol 87 n° 6 (June 2013)
PermalinkGPS snow depth meter with geometry-free linear combinations of carrier phases / M. Ozeki in Journal of geodesy, vol 86 n° 3 (March 2012)
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