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A constrained extended Kalman filter based on LS-VCE formulated by condition equations with prediction of cross-covariances / Vahid Mahboub in Survey review, Vol 53 n° 380 (September 2021)  

Public [article]  inSurvey review > Vol 53 n° 380 (September 2021) . - pp 422 - 435 Titre : A constrained extended Kalman filter based on LS-VCE formulated by condition equations with prediction of cross-covariances Type de document : Article/Communication Auteurs : Vahid Mahboub, Auteur ; Narges Fatholahi, Auteur Année de publication : 2021 Article en page(s) : pp 422 - 435 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géodésie spatiale [Termes IGN] algorithme de filtrage [Termes IGN] analyse de variance [Termes IGN] filtre adaptatif [Termes IGN] filtre de Kalman [Termes IGN] matrice de covariance [Termes IGN] méthode des moindres carrés [Termes IGN] modèle non linéaire [Termes IGN] modèle stochastique Résumé : (auteur) A constrained extended Kalman filter (CEKF) based on least-squares variance component estimation (LS-VCE) is generally developed by condition equations since the proper prediction of dispersion matrices is one of the main bottlenecks in the KF algorithms. Here we investigate four problems which have not been simultaneously considered yet. These problems are examination of non-linearty of dynamic model, VCE, general non-linear state constraints and fairly general stochastic model. Although a few contributions proposed some adaptive KF in particular based on Helmert’s VCE method, they developed their filters for special problems with some restrictive conditions such as independence of all variables and/or linearity of the dynamic model. Also some of these filters did not apply VCE methods to all parts of the dynamic model. In this contribution, we try to overcome all of these restrictions. Moreover, LS-VCE method gives some added advantages over other VCE methods. First the new formulation of CEKF is developed by condition equations with prediction of all possible cross-covariances as algorithm 1. Then the LS-VCE method is applied to it after some modifications which results in an adaptive constrained extended Kalman filter (ACEKF) as the second algorithm. Numéro de notice : A2021-636 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/00396265.2020.1814030 Date de publication en ligne : 07/09/2020 En ligne : https://doi.org/10.1080/00396265.2020.1814030 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98300 [article]

Deformation analysis of a reference wall towards the uncertainty investigation of terrestrial laser scanners / Berit Schmitz in Journal of applied geodesy, vol 15 n° 3 (July 2021)  

Public [article]  inJournal of applied geodesy > vol 15 n° 3 (July 2021) . - pp 189-206 Titre : Deformation analysis of a reference wall towards the uncertainty investigation of terrestrial laser scanners Type de document : Article/Communication Auteurs : Berit Schmitz, Auteur ; Heiner Kuhlmann, Auteur ; Christoph Holst, Auteur Année de publication : 2021 Article en page(s) : pp 189-206 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] déformation d'édifice [Termes IGN] déformation géométrique [Termes IGN] données laser [Termes IGN] incertitude géométrique [Termes IGN] matrice de covariance [Termes IGN] modèle de déformation tectonique [Termes IGN] modèle stochastique [Termes IGN] mur [Termes IGN] qualité des données [Termes IGN] tachéomètre électronique [Termes IGN] télémètre laser terrestre Résumé : (Auteur) The perfect knowledge about the scanned object’s geometry is essential for the empirical analysis of the stochastic properties of terrestrial laser scanners (TLSs). The Bonn reference wall is intended to be used as a reference for TLS quality investigations. Therefore, it is necessary to know the geometry of the wall at each time of scanning to avoid the misinterpretation of possible movements as systematic effects in the scanner. For this reason, we investigate the stability of the Bonn reference wall in this study. This includes the definition of a geodetic datum, the quantification of displacements, and the establishment of a suited deformation model. Since we discover a movement of about 1 mm within one day and up to 7 mm over the year, it is necessary to establish a cause-response deformation model to correct the wall movements in the scans. This study proposes two dynamic deformation models to compensate for the movements of the wall within one day and within a year. Our results show that it is better to measure the initial geometry of the wall each day since 89 % of the relative movements can be reduced to a maximum of 0.25 mm with a standard deviation of 0.16 mm (0.23 mm without modeling). If the shape is not initially known each day, the standard deviation of the displacements can be reduced from 1.10 mm to 0.61 mm, but the largest residuals still amount up to 2.5 mm, which is not sufficient for stochastic TLS investigations. Numéro de notice : A2021-467 Affiliation des auteurs : non IGN Thématique : IMAGERIE/POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1515/jag-2020-0025 Date de publication en ligne : 25/03/2021 En ligne : https://doi.org/10.1515/jag-2020-0025 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98103 [article]

Forest height estimation from a robust TomoSAR method in the case of small tomographic aperture with airborne dataset at L-band / Xing Peng in Remote sensing, vol 13 n° 11 (June-1 2021)  

Public [article]  inRemote sensing > vol 13 n° 11 (June-1 2021) . - n° 2147 Titre : Forest height estimation from a robust TomoSAR method in the case of small tomographic aperture with airborne dataset at L-band Type de document : Article/Communication Auteurs : Xing Peng, Auteur ; Xinwu Li, Auteur ; Yanan Du, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : n° 2147 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] bande L [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] données TomoSAR [Termes IGN] forêt boréale [Termes IGN] hauteur des arbres [Termes IGN] image 3D [Termes IGN] image radar moirée [Termes IGN] inventaire forestier (techniques et méthodes) [Termes IGN] itération [Termes IGN] matrice de covariance [Termes IGN] modèle numérique de surface de la canopée [Termes IGN] semis de points [Termes IGN] Suède [Termes IGN] tomographie radar Résumé : (auteur) Forest height is an essential input parameter for forest biomass estimation, ecological modeling, and the carbon cycle. Tomographic synthetic aperture radar (TomoSAR), as a three-dimensional imaging technique, has already been successfully used in forest areas to retrieve the forest height. The nonparametric iterative adaptive approach (IAA) has been recently introduced in TomoSAR, achieving a good compromise between high resolution and computing efficiency. However, the performance of the IAA algorithm is significantly degraded in the case of a small tomographic aperture. To overcome this shortcoming, this paper proposes the robust IAA (RIAA) algorithm for SAR tomography. The proposed approach follows the framework of the IAA algorithm, but also considers the noise term in the covariance matrix estimation. By doing so, the condition number of the covariance matrix can be prevented from being too large, improving the robustness of the forest height estimation with the IAA algorithm. A set of simulated experiments was carried out, and the results validated the superiority of the RIAA estimator in the case of a small tomographic aperture. Moreover, a number of fully polarimetric L-band airborne tomographic SAR images acquired from the ESA BioSAR 2008 campaign over the Krycklan Catchment, Northern Sweden, were collected for test purposes. The results showed that the RIAA algorithm performed better in reconstructing the vertical structure of the forest than the IAA algorithm in areas with a small tomographic aperture. Finally, the forest height was estimated by both the RIAA and IAA TomoSAR methods, and the estimation accuracy of the RIAA algorithm was 2.01 m, which is more accurate than the IAA algorithm with 3.25 m. Numéro de notice : A2021-441 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.3390/rs13112147 Date de publication en ligne : 29/05/2021 En ligne : https://doi.org/10.3390/rs13112147 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97828 [article]

Gauss-Markov model with random parameters to adjust results of surveys of geodetic control networks / Marek Banas in Reports on geodesy and geoinformatics, vol 111 n° 1 (June 2021)  

Public [article]  inReports on geodesy and geoinformatics > vol 111 n° 1 (June 2021) Titre : Gauss-Markov model with random parameters to adjust results of surveys of geodetic control networks Type de document : Article/Communication Auteurs : Marek Banas, Auteur ; Jozef Czaja, Auteur ; Janusz Dabrowski, Auteur Année de publication : 2021 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] matrice de covariance [Termes IGN] modèle de Gauss-Markov [Termes IGN] point de nivellement [Termes IGN] réseau de contrôle Résumé : (auteur) Alignment of an engineering object project in the field is always conducted at the points of the geodetic control network, the coordinates of which are determined on the basis of the results of its elements survey and with connection to the national spatial reference system. The points of the national spatial reference system determined on the basis of previous surveys have specified coordinates with adequate accuracy, which is included in their covariance matrix. The coordinates of the geodetic control network points are determined more accurately than the points of the national spatial reference system and this means that the results of surveys of the geodetic control network have to be adequately incorporated into the coordinates of the reference points. In order to perform this incorporation, it may be assumed that the coordinates of the reference points are random, that is, they have a covariance matrix, which should be used in the process of adjusting the results of the geodetic control network observation. This research paper presents the principles for the estimation of the Gauss-Markov model parameters applied in case of those geodetic control networks in which the coordinates of the reference points have random character. On the basis of the observation equations δ + AX = L for the geodetic control network and using the weighting matrix P and the matrix of conditional covariances (P−1 + ACXAT) for the observation vector L, the parameter vector X is estimated in the form of the derived formula X^=(CX−1+ATPA)−1ATP⋅L . The verification of these estimation principles has been illustrated by the example of a fragment of a levelling geodetic control network consisting of three geodetic control points and two reference points of the national spatial reference system. The novel feature of the proposed solution is the application of covariance matrices of the reference point coordinates to adjust the results of the survey of geodetic control networks and to determine limit standard deviations for the estimated coordinates of geodetic control network points. Numéro de notice : A2021-780 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article DOI : 10.2478/rgg-2021-0001 En ligne : https://doi.org/10.2478/rgg-2021-0001 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98797 [article]

PolSAR ship detection based on neighborhood polarimetric covariance matrix / Tao Liu in IEEE Transactions on geoscience and remote sensing, vol 59 n° 6 (June 2021)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 59 n° 6 (June 2021) . - pp 4874 - 4887 Titre : PolSAR ship detection based on neighborhood polarimetric covariance matrix Type de document : Article/Communication Auteurs : Tao Liu, Auteur ; Ziyuan Yang, Auteur ; Armando Marino, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 4874 - 4887 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications [Termes IGN] détection d'objet [Termes IGN] données polarimétriques [Termes IGN] image radar moirée [Termes IGN] image Radarsat [Termes IGN] matrice de covariance [Termes IGN] navire [Termes IGN] polarimétrie radar [Termes IGN] voisinage (topologie) Résumé : (auteur) The detection of small ships in polarimetric synthetic aperture radar (PolSAR) images is still a topic for further investigation. Recently, patch detection techniques, such as superpixel-level detection, have stimulated wide interest because they can use the information contained in similarities among neighboring pixels. In this article, we propose a novel neighborhood polarimetric covariance matrix (NPCM) to detect the small ships in PolSAR images, leading to a significant improvement in the separability between ship targets and sea clutter. The NPCM utilizes the spatial correlation between neighborhood pixels and maps the representation for a given pixel into a high-dimensional covariance matrix by embedding spatial and polarization information. Using the NPCM formalism, we apply a standard whitening filter, similar to the polarimetric whitening filter (PWF). We show how the inclusion of neighborhood information improves the performance compared with the traditional polarimetric covariance matrix. However, this is at the expense of a higher computation cost. The theory is validated via the simulated and measured data under different sea states and using different radar platforms. Numéro de notice : A2021-424 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2020.3022181 Date de publication en ligne : 22/09/2020 En ligne : https://doi.org/10.1109/TGRS.2020.3018638 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97780 [article]

High-resolution geoid modeling using least squares modification of Stokes and Hotine formulas in Colorado / Mustafa Serkan Işık in Journal of geodesy, vol 95 n° 5 (May 2021)  

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Stochastic model reliability in GNSS baseline solution / Aviram Borko in Journal of geodesy, vol 95 n° 2 (February 2021)  

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Impact of INSAT-3D/3DR radiance data assimilation in predicting tropical cyclone Titli over the bay of Bengal / Raghu Nadimpalli in IEEE Transactions on geoscience and remote sensing, vol 58 n° 10 (October 2020)  

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Stochastic modeling for VRS network-based GNSS RTK with residual interpolation uncertainty / Thanate Jongrujinan in Journal of applied geodesy, vol 14 n° 3 (July 2020)  

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A point cloud feature regularization method by fusing judge criterion of field force / Xijiang Chen in IEEE Transactions on geoscience and remote sensing, vol 58 n° 5 (May 2020)  

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Deep SAR-Net: learning objects from signals / Zhongling Huang in ISPRS Journal of photogrammetry and remote sensing, vol 161 (March 2020)  

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2014 Hartebeesthoek co-location survey reprocessing report / Jean-Michaël Muller (2020) 

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Approche bayésienne pour la sélection de modèles / Benjamin Harroué (2020)  

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Identification of alpine glaciers in the central Himalayas using fully polarimetric L-Band SAR data / Guo-Hui Yao in IEEE Transactions on geoscience and remote sensing, vol 58 n° 1 (January 2020)  

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The certitude of a global sea level acceleration during the satellite altimeter era / Huseyin Baki Iz in Journal of geodetic science, vol 10 n° 1 (January 2020)  

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