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Tropospheric and range biases in Satellite Laser Ranging / Mateusz Drożdżewski in Journal of geodesy, vol 95 n° 9 (September 2021)
[article]
Titre : Tropospheric and range biases in Satellite Laser Ranging Type de document : Article/Communication Auteurs : Mateusz Drożdżewski, Auteur ; Krzysztof Sosnica, Auteur Année de publication : 2021 Article en page(s) : n° 100 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géodésie spatiale
[Termes IGN] champ de pesanteur terrestre
[Termes IGN] correction troposphérique
[Termes IGN] données Lageos
[Termes IGN] données TLS (télémétrie)
[Termes IGN] erreur systématique
[Termes IGN] géocentre
[Termes IGN] harmonique sphérique
[Termes IGN] retard troposphérique zénithal
[Termes IGN] télémétrie laser sur satelliteRésumé : (auteur) The Satellite Laser Ranging (SLR) technique provides very accurate distance measurements to artificial Earth satellites. SLR is employed for the realization of the origin and the scale of the terrestrial reference frame. Despite the high precision, SLR observations can be affected by various systematic errors. So far, range biases were used to account for systematic measurement errors and mismodeling effects in SLR. Range biases are constant for all elevation angles and independent of the measured distance to a satellite. Recently, intensity-dependent biases for single-photon SLR detectors and offsets of barometer readings and meteorological devices were reported for some SLR stations. In this paper, we study the possibility of the direct estimation of tropospheric biases from SLR observations to LAGEOS satellites. We discuss the correlations between the station heights, range biases, tropospheric biases, and their impact on the repeatability of station coordinates, geocenter motion, and the global scale of the reference frame. We found that the solution with the estimation of tropospheric biases provides more stable station coordinates than the solution with the estimation of range biases. From the common estimation of range and tropospheric biases, we found that most of the systematic effects at SLR stations are better absorbed by elevation-dependent tropospheric biases than range biases which overestimate the total bias effect. The estimation of tropospheric biases changes the SLR-derived global scale by 0.3 mm and the geocenter coordinates by 1 mm for the Z component, causing thus an offset in the realization of the reference frame origin. Estimation of range biases introduces an offset in some SLR-derived low-degree spherical harmonics of the Earth’s gravity field. Therefore, considering elevation-dependent tropospheric and intensity biases is essential for deriving high-accuracy geodetic parameters. Numéro de notice : A2021-621 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s00190-021-01554-0 Date de publication en ligne : 21/08/2021 En ligne : https://doi.org/10.1007/s00190-021-01554-0 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98237
in Journal of geodesy > vol 95 n° 9 (September 2021) . - n° 100[article]Variational bayesian compressive multipolarization indoor radar imaging / Van Ha Tang in IEEE Transactions on geoscience and remote sensing, Vol 59 n° 9 (September 2021)
[article]
Titre : Variational bayesian compressive multipolarization indoor radar imaging Type de document : Article/Communication Auteurs : Van Ha Tang, Auteur ; Abdesselam Bouzerdoum, Auteur ; Son Lam Phung, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 7459 - 7474 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications
[Termes IGN] acquisition comprimée
[Termes IGN] détection à travers-le-mur
[Termes IGN] estimation bayesienne
[Termes IGN] fouillis d'échos
[Termes IGN] image radar
[Termes IGN] inférence statistique
[Termes IGN] modèle stochastique
[Termes IGN] polarisation
[Termes IGN] positionnement en intérieur
[Termes IGN] reconstruction d'imageRésumé : (auteur) This article introduces a probabilistic Bayesian model for addressing the problem of compressive multipolarization through-wall radar imaging (TWRI). The proposed approach formulates the task of wall-clutter mitigation and multipolarization image reconstruction as a Bayesian inference problem for a joint distribution between observed radar measurements and latent wall-clutter matrix and indoor target images. The joint probability distribution incorporates three prior beliefs: low-dimensional structure of the wall reflections, group sparsity structure of the target images, and joint sparsity among the polarization images. These signal attributes are modeled through hierarchical priors, whose parameters and hyperparameters are treated with a full Bayesian formulation. Furthermore, this article presents a variational Bayesian inference algorithm that estimates wall-clutter and multipolarization images as posterior distributions and optimizes the model parameters and hyperparameters simultaneously. Experimental results on simulated and real radar data show that the proposed model is very effective at removing wall clutter and enhancing target localization even when the radar measurements are significantly reduced. Numéro de notice : A2021-647 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2021.3051955 Date de publication en ligne : 26/01/2021 En ligne : https://doi.org/10.1109/TGRS.2021.3051955 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98354
in IEEE Transactions on geoscience and remote sensing > Vol 59 n° 9 (September 2021) . - pp 7459 - 7474[article]Visualization of GNSS multipath effects and its potential application in IGS data processing / Weiming Tang in Journal of geodesy, vol 95 n° 9 (September 2021)
[article]
Titre : Visualization of GNSS multipath effects and its potential application in IGS data processing Type de document : Article/Communication Auteurs : Weiming Tang, Auteur ; Yawei Wang, Auteur ; Xuan Zou, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : n° 103 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] grille
[Termes IGN] interférence
[Termes IGN] international GPS service for geodynamics
[Termes IGN] modèle d'erreur
[Termes IGN] phase
[Termes IGN] positionnement cinématique
[Termes IGN] qualité des données
[Termes IGN] trajet multiple
[Vedettes matières IGN] Traitement de données GNSSRésumé : (auteur) A modified multipath error mitigation method using the multi-point hemispherical grid model (MHGM) is proposed, and the influence of changes in the observation environments of IGS stations on their data quality is evaluated. The multipath error models of different satellite pairs for different observation periods can be established using the integrated multi-GNSS data in the proposed method. The test under deliberate high multipath environment reveals that this method can effectively estimate the GNSS multipath error, detect and present the orientation of the interference sources around the station. The RMS of residuals and the kinematic positioning accuracy on day 237 of 2018 are improved by 68% and 61%, respectively. Compared with the empirical site model (ESM), which can also visualize the effects of the multipath, the RMS of residuals when applying the MHGM is improved by 20%. The test with IGS historical observations shows that MHGM can effectively reflect the influence of changing multipath interference around stations on carrier phase observations, with an average improvement of 25% in the RMS of carrier phase residuals in the extrapolated 9-day validations over the past 18 years. The results of a kinematic positioning experiment in 2019 generally coincide with the RMS statistic results of carrier phase residuals as well. The MHGM demonstrates distinct potential in the influence evaluation of changes for the multipath interference around the stations on their observation quality. Numéro de notice : A2021-625 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s00190-021-01559-9 Date de publication en ligne : 28/08/2021 En ligne : https://doi.org/10.1007/s00190-021-01559-9 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98249
in Journal of geodesy > vol 95 n° 9 (September 2021) . - n° 103[article]Unsupervised band selection of hyperspectral data based on mutual information derived from weighted cluster entropy for snow classification / Divyesh Varade in Geocarto international, vol 36 n° 15 ([15/08/2021])
[article]
Titre : Unsupervised band selection of hyperspectral data based on mutual information derived from weighted cluster entropy for snow classification Type de document : Article/Communication Auteurs : Divyesh Varade, Auteur ; Ajay K. Maurya, Auteur ; Onkar Dikshit, Auteur Année de publication : 2021 Article en page(s) : pp 1709 - 1731 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse de groupement
[Termes IGN] bande spectrale
[Termes IGN] classification floue
[Termes IGN] classification par forêts d'arbres décisionnels
[Termes IGN] classification par nuées dynamiques
[Termes IGN] distribution spatiale
[Termes IGN] entropie
[Termes IGN] image EO1-Hyperion
[Termes IGN] image hyperspectrale
[Termes IGN] Inde
[Termes IGN] manteau neigeux
[Termes IGN] neige
[Termes IGN] réflectance spectraleRésumé : (auteur) Information on the spatial and temporal extent of snow cover distribution is a significant input in hydrological processes and climate models. Although hyperspectral remote sensing provides significant opportunities in the assessment of land cover, the applications of such data are limited in the snow-covered alpine regions. A major issue with hyperspectral data is the larger dimensionality. Feature selection methods are often used to derive the most informative subset of bands from the hyperspectral data. In this study, a band selection technique is proposed which utilizes the mutual information (MI) between hyperspectral bands and a reference band. The first principal component of the hyperspectral data is selected as the reference band. Two variants of this approach are proposed involving preclustering of bands using: (1) the k-means and (2) the fuzzy k-means algorithms. The MI is derived from weighted entropy of the hyperspectral band and the reference band. The weights are computed from the cluster distance ratio and the cluster membership function for the k-means and fuzzy k-means algorithm, respectively. The selected bands were classified using random forest classifier. The proposed methods are evaluated with four datasets, two Hyperion datasets corresponding to the geographical locations of Dhundi and Solang in India, corresponding to snow covered terrain and two benchmark AVIRIS datasets of Indian Pines and Salinas. The average classification accuracy (0.995 and 0.721 for Dhundi and Solang datasets, respectively) for the proposed approach were observed to be better as compared with those from other state of the art techniques. Numéro de notice : A2021-568 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2019.1665717 Date de publication en ligne : 18/09/2019 En ligne : https://doi.org/10.1080/10106049.2019.1665717 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98183
in Geocarto international > vol 36 n° 15 [15/08/2021] . - pp 1709 - 1731[article]Background segmentation in multicolored illumination environments / Nikolas Ladas in The Visual Computer, vol 37 n° 8 (August 2021)
[article]
Titre : Background segmentation in multicolored illumination environments Type de document : Article/Communication Auteurs : Nikolas Ladas, Auteur ; Paris Kaimakis, Auteur ; Yiorgos Chrysanthou, Auteur Année de publication : 2021 Article en page(s) : pp 2221 - 2233 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] classification pixellaire
[Termes IGN] détection d'ombre
[Termes IGN] éclairage
[Termes IGN] éclairement lumineux
[Termes IGN] modèle stochastique
[Termes IGN] objectif grand angulaire
[Termes IGN] réflectance
[Termes IGN] segmentation d'imageRésumé : (auteur) We present an algorithm for the segmentation of images into background and foreground regions. The proposed algorithm utilizes a physically based formulation of scene appearance which explicitly models the formation of shadows originating from color light sources. This formulation enables a probabilistic model to distinguish between shadows and foreground objects in challenging images. A key component of the proposed method is an algorithm for estimating the illumination arriving at the scene. We evaluate our algorithm using synthetic and real-world data and show that the proposed method performs favorably against other commonly used segmentation methods. Numéro de notice : A2021-596 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1007/s00371-020-01981-8 Date de publication en ligne : 06/10/2020 En ligne : https://doi.org/10.1007/s00371-020-01981-8 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98225
in The Visual Computer > vol 37 n° 8 (August 2021) . - pp 2221 - 2233[article]Estimation of code observation-specific biases (OSBs) for the modernized multi-frequency and multi-GNSS signals: an undifferenced and uncombined approach / Teng Liu in Journal of geodesy, vol 95 n° 8 (August 2021)PermalinkEstimation of surface deformation due to Pasni earthquake using RADAR interferometry / Muhammad Ali in Geocarto international, vol 36 n° 14 ([01/08/2021])PermalinkImproving urban land cover classification with combined use of Sentinel-2 and Sentinel-1 imagery / Bin Hu in ISPRS International journal of geo-information, vol 10 n° 8 (August 2021)PermalinkSpatiotemporal analysis of urban heat island intensification in the city of Minneapolis-St. Paul and Chicago metropolitan areas using Landsat data from 1984 to 2016 / Mbongowo J. Mbuh in Geocarto international, vol 36 n° 14 ([01/08/2021])PermalinkAtmospheric correction to passive microwave brightness temperature in snow cover mapping over china / Yubao Qiu in IEEE Transactions on geoscience and remote sensing, vol 59 n° 8 (August 2021)PermalinkLeaf and wood separation for individual trees using the intensity and density data of terrestrial laser scanners / Kai Tan in IEEE Transactions on geoscience and remote sensing, vol 59 n° 8 (August 2021)PermalinkThree-dimensional reconstruction of seismo-traveling ionospheric disturbances after March 11, 2011, Japan Tohoku earthquake / Changzhi Zhai in Journal of geodesy, vol 95 n° 7 (July 2021)PermalinkComparison of polar ionospheric behavior at Arctic and Antarctic regions for improved satellite-based positioning / Arun Kumar Singh in Journal of applied geodesy, vol 15 n° 3 (July 2021)PermalinkDetecting high-temperature anomalies from Sentinel-2 MSI images / Yongxue Liu in ISPRS Journal of photogrammetry and remote sensing, vol 177 (July 2021)PermalinkExtracting Shallow-Water Bathymetry from Lidar point clouds using pulse attribute data: Merging density-based and machine learning approaches / Kim Lowell in Marine geodesy, vol 44 n° 4 (July 2021)Permalink