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Multivariate analysis of GPS position time series of JPL second reprocessing campaign / AliReza Amiri-Simkooei in Journal of geodesy, vol 91 n° 6 (June 2017)
[article]
Titre : Multivariate analysis of GPS position time series of JPL second reprocessing campaign Type de document : Article/Communication Auteurs : AliReza Amiri-Simkooei, Auteur ; T.H. Mohammadloo, Auteur ; Donald F. Argus, Auteur Année de publication : 2017 Article en page(s) : pp 685 - 704 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] analyse multivariée
[Termes IGN] bruit blanc
[Termes IGN] bruit rose
[Termes IGN] campagne GPS
[Termes IGN] centre de phase
[Termes IGN] coordonnées GPS
[Termes IGN] série temporelle
[Termes IGN] terme de Chandler
[Vedettes matières IGN] Traitement de données GNSSRésumé : (Auteur) The second reprocessing of all GPS data gathered by the Analysis Centers of IGS was conducted in late 2013 using the latest models and methodologies. Improved models of antenna phase center variations and solar radiation pressure in JPL’s reanalysis are expected to significantly reduce errors. In an earlier work, JPL estimates of position time series, termed first reprocessing campaign, were examined in terms of their spatial and temporal correlation, power spectra, and draconitic signal. Similar analyses are applied to GPS time series at 89 and 66 sites of the second reanalysis with the time span of 7 and 21 years, respectively, to study possible improvements. Our results indicate that the spatial correlations are reduced on average by a factor of 1.25. While the white and flicker noise amplitudes for all components are reduced by 29–56 %, the random walk amplitude is enlarged. The white, flicker, and random walk noise amount to rate errors of, respectively, 0.01, 0.12, and 0.09 mm/yr in the horizontal and 0.04, 0.41 and 0.3 mm/yr in the vertical. Signals reported previously, such as those with periods of 13.63, 14.76, 5.5, and 351.4 / n for n=1,2,…,8 days, are identified in multivariate spectra of both data sets. The oscillation of the draconitic signal is reduced by factors of 1.87, 1.87, and 1.68 in the east, north and up components, respectively. Two other signals with Chandlerian period and a period of 380 days can also be detected. Numéro de notice : A2017-297 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s00190-016-0991-9 En ligne : http://dx.doi.org/10.1007/s00190-016-0991-9 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=85328
in Journal of geodesy > vol 91 n° 6 (June 2017) . - pp 685 - 704[article]Analytical and numerical investigations on the accuracy and robustness of geometric features extracted from 3D point cloud data / André Dittrich in ISPRS Journal of photogrammetry and remote sensing, vol 126 (April 2017)
[article]
Titre : Analytical and numerical investigations on the accuracy and robustness of geometric features extracted from 3D point cloud data Type de document : Article/Communication Auteurs : André Dittrich, Auteur ; Martin Weinmann, Auteur ; Stefan Hinz, Auteur Année de publication : 2017 Article en page(s) : pp 195 – 208 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques
[Termes IGN] bruit (théorie du signal)
[Termes IGN] calcul tensoriel
[Termes IGN] discrétisation
[Termes IGN] données localisées 3D
[Termes IGN] extraction automatique
[Termes IGN] extraction de traits caractéristiques
[Termes IGN] lasergrammétrie
[Termes IGN] méthode robuste
[Termes IGN] restitution lasergrammétrique
[Termes IGN] semis de points
[Termes IGN] valeur propreRésumé : (auteur) In photogrammetry, remote sensing, computer vision and robotics, a topic of major interest is represented by the automatic analysis of 3D point cloud data. This task often relies on the use of geometric features amongst which particularly the ones derived from the eigenvalues of the 3D structure tensor (e.g. the three dimensionality features of linearity, planarity and sphericity) have proven to be descriptive and are therefore commonly involved for classification tasks. Although these geometric features are meanwhile considered as standard, very little attention has been paid to their accuracy and robustness. In this paper, we hence focus on the influence of discretization and noise on the most commonly used geometric features. More specifically, we investigate the accuracy and robustness of the eigenvalues of the 3D structure tensor and also of the features derived from these eigenvalues. Thereby, we provide both analytical and numerical considerations which clearly reveal that certain features are more susceptible to discretization and noise whereas others are more robust. Numéro de notice : A2017-117 Affiliation des auteurs : non IGN Thématique : IMAGERIE/INFORMATIQUE/MATHEMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2017.02.012 En ligne : http://dx.doi.org/10.1016/j.isprsjprs.2017.02.012 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=84512
in ISPRS Journal of photogrammetry and remote sensing > vol 126 (April 2017) . - pp 195 – 208[article]Réservation
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[article]
Titre : Modified residual method for the estimation of noise in hyperspectral images Type de document : Article/Communication Auteurs : Asad Mahmood, Auteur ; Amandine Robin, Auteur ; Michael Sears, Auteur Année de publication : 2017 Article en page(s) : pp 1451 - 1460 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] bande spectrale
[Termes IGN] bruit blanc
[Termes IGN] corrélation
[Termes IGN] corrélation automatique de points homologues
[Termes IGN] filtrage du bruit
[Termes IGN] image hyperspectrale
[Termes IGN] matrice de covariance
[Termes IGN] résiduRésumé : (Auteur) Many hyperspectral image processing algorithms (e.g., detection, classification, endmember extraction, and so on) are generally designed with the assumption of no spectral or spatial correlation in noise. However, previous studies have shown the presence of nonnegligible correlation between the noise samples in different spectral bands, especially between noises in adjacent bands, and that most of the well-known intrinsic dimension estimation algorithms give poor estimates in the presence of correlated noise. Thus, there is a need to tackle the specific case of spectrally correlated noise for noise estimation. We show, in this paper, that the commonly employed hyperspectral noise estimation algorithm based on regression residuals can be significantly affected by spectrally correlated noise and we suggest a modified approach that proves to be robust to noise correlation. Furthermore, the proposed method improves the noise variance estimates in comparison to the classic residual method even for the case of uncorrelated noise. Simulation results show that the estimation error is reduced at times by a factor of 5 when there is high spectral correlation in the noise. Our proposed per-pixel noise estimator requires an estimate of the noise covariance matrix, and for this, we also propose a method to estimate the noise covariance matrix. Simulation results demonstrate that the per-pixel noise estimates obtained via the use of estimated noise statistics are almost as good as those obtained via use of the true statistics. Numéro de notice : A2017-155 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2016.2624505 En ligne : http://dx.doi.org/10.1109/TGRS.2016.2624505 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=84690
in IEEE Transactions on geoscience and remote sensing > vol 55 n° 3 (March 2017) . - pp 1451 - 1460[article]Study of the effects on GPS coordinate time series caused by higher-order ionospheric corrections calculated using the DIPOLE model / Liansheng Deng in Geodesy and Geodynamics, vol 8 n° 2 (March 2017)
[article]
Titre : Study of the effects on GPS coordinate time series caused by higher-order ionospheric corrections calculated using the DIPOLE model Type de document : Article/Communication Auteurs : Liansheng Deng, Auteur ; Weiping Jiang, Auteur ; Hua Chen, Auteur ; Zhaohan Zhu, Auteur ; Wen Zhao, Auteur Année de publication : 2017 Article en page(s) : pp 111 - 119 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] amplitude
[Termes IGN] bruit blanc
[Termes IGN] bruit rose
[Termes IGN] champ géomagnétique
[Termes IGN] correction ionosphérique
[Termes IGN] GAMIT
[Termes IGN] GLOBK
[Termes IGN] série temporelle
[Vedettes matières IGN] Traitement de données GNSSRésumé : (auteur) As one of the main error sources in high-precision Global Positioning System (GPS) data processing, higher-order ionospheric (HOI) delays cause significant effects on coordinate time series that cannot be ignored in analyses of long time series. Typically two geomagnetic models, DIPOLE model and International Geomagnetic Reference Field (IGRF) model, are used for calculating HOI corrections. This paper investigates the effects of HOI correction caused by the DIPOLE model on coordinate time series. GPS data from 104 globally distributed International GNSS Service (IGS) stations spanning from January, 1999 to December, 2003 were reprocessed following up-to-date processing strategies utilizing GAMIT and GLOBK software. Two coordinate time series solutions before and after applying HOI corrections using the DIPOLE model were derived for studying the effects in terms of seasonal variations and noise amplitudes. The results show that after applying the HOI corrections calculated with DIPOLE, the noise amplitudes of the coordinate time series increased, especially in the north and east directions, and the increased amplitudes of the flicker noise were larger than those of the white noise. Furthermore, spurious periodic signals that were probably introduced by the HOI corrections from the DIPOLE model were also found. Moreover, an apparent increase was confirmed for the power spectra of most of the stations, especially in the north direction, and the amplitudes of both the annual and semi-annual signals also increased in the north and east directions. It can be inferred that the quality of the external data sources such as the geomagnetic model might be the key factors that lead to the above results. The results also suggest that we should be very careful when the DIPOLE model is used for HOI corrections. Numéro de notice : A2017-235 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article DOI : 10.1016/j.geog.2017.01.004 En ligne : https://doi.org/10.1016/j.geog.2017.01.004 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=85167
in Geodesy and Geodynamics > vol 8 n° 2 (March 2017) . - pp 111 - 119[article]Determination of a terrestrial reference frame via Kalman filtering of very long baseline interferometry data / Benedikt Soja in Journal of geodesy, vol 90 n° 12 (December 2016)
[article]
Titre : Determination of a terrestrial reference frame via Kalman filtering of very long baseline interferometry data Type de document : Article/Communication Auteurs : Benedikt Soja, Auteur ; Tobias Nilsson, Auteur ; Kyriakos Balidakis, Auteur ; et al., Auteur Année de publication : 2016 Article en page(s) : pp 1311 - 1327 Note générale : Bibliographie ; Erratum : voir pdf Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Systèmes de référence et réseaux
[Termes IGN] bruit (théorie du signal)
[Termes IGN] coordonnées géographiques
[Termes IGN] filtre de Kalman
[Termes IGN] image radar moirée
[Termes IGN] interférométrie à très grande base
[Termes IGN] International Terrestrial Reference Frame
[Termes IGN] modèle stochastique
[Termes IGN] station permanenteRésumé : (Auteur) Terrestrial reference frames (TRF), such as the ITRF2008, are primary products of geodesy. In this paper, we present TRF solutions based on Kalman filtering of very long baseline interferometry (VLBI) data, for which we estimate steady station coordinates over more than 30 years that are updated for every single VLBI session. By applying different levels of process noise, non-linear signals, such as seasonal and seismic effects, are taken into account. The corresponding stochastic model is derived site-dependent from geophysical loading deformation time series and is adapted during periods of post-seismic deformations. Our results demonstrate that the choice of stochastic process has a much smaller impact on the coordinate time series and velocities than the overall noise level. If process noise is applied, tests with and without additionally estimating seasonal signals indicate no difference between the resulting coordinate time series for periods when observational data are available. In a comparison with epoch reference frames, the Kalman filter solutions provide better short-term stability. Furthermore, we find out that the Kalman filter solutions are of similar quality when compared to a consistent least-squares solution, however, with the enhanced attribute of being easier to update as, for instance, in a post-earthquake period. Numéro de notice : A2016-804 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s00190-016-0924-7 En ligne : http://dx.doi.org/10.1007/s00190-016-0924-7 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=82591
in Journal of geodesy > vol 90 n° 12 (December 2016) . - pp 1311 - 1327[article]Dictionary learning for promoting structured sparsity in hyperspectral compressive sensing / Lei Zhang in IEEE Transactions on geoscience and remote sensing, vol 54 n° 12 (December 2016)PermalinkOn the spectral combination of satellite gravity model, terrestrial and airborne gravity data for local gravimetric geoid computation / Tao Jian in Journal of geodesy, vol 90 n° 12 (December 2016)PermalinkOn the significance of periodic signals in noise analysis of GPS station coordinates time series / Janusz Bogusz in GPS solutions, vol 20 n° 4 (October 2016)PermalinkNoise removal from hyperspectral image with joint spectral–spatial distributed sparse representation / Jie Li in IEEE Transactions on geoscience and remote sensing, vol 54 n° 9 (September 2016)PermalinkAn adaptive stochastic model for GPS observations and its performance in precise point positioning / J. Z. Zheng in Survey review, vol 48 n° 349 (July 2016)PermalinkEstimating the intrinsic dimension of hyperspectral images using a noise-whitened eigengap approach / Abderrahim Halimi in IEEE Transactions on geoscience and remote sensing, vol 54 n° 7 (July 2016)PermalinkTowards reliable velocities of permanent GNSS stations / Janusz Bogusz in Reports on geodesy and geoinformatics, vol 100 (May 2016)PermalinkChange detection between SAR images using a pointwise approach and graph theory / Minh-Tan Pham in IEEE Transactions on geoscience and remote sensing, vol 54 n° 4 (April 2016)PermalinkTemporal MODIS data for identification of wheat crop using noise clustering soft classification approach / Priyadarshi Upadhyay in Geocarto international, vol 31 n° 3 - 4 (March - April 2016)PermalinkCaractérisation des signaux et des bruits des séries temporelles du géocentre et des paramètres de rotation de la Terre (EOP) / Bachir Gourine in Bulletin des sciences géographiques, n° 30 (2015 - 2016)Permalink