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Assessment of inner reliability in the Gauss-Helmert model / Andreas Ettlinger in Journal of applied geodesy, vol 14 n° 1 (January 2020)  

Public [article]  inJournal of applied geodesy > vol 14 n° 1 (January 2020) . - pp 13 - 28 Titre : Assessment of inner reliability in the Gauss-Helmert model Type de document : Article/Communication Auteurs : Andreas Ettlinger, Auteur ; Hans Neuner, Auteur Année de publication : 2020 Article en page(s) : pp 13 - 28 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géodésie [Termes descripteurs IGN] coefficient de corrélation [Termes descripteurs IGN] compensation par moindres carrés [Termes descripteurs IGN] détection d'erreur [Termes descripteurs IGN] erreur systématique [Termes descripteurs IGN] fiabilité des données [Termes descripteurs IGN] filtre de Kalman [Termes descripteurs IGN] modèle d'erreur [Termes descripteurs IGN] modèle de Gauss-Helmert [Termes descripteurs IGN] valeur aberrante Résumé : (auteur) In this contribution, the minimum detectable bias (MDB) as well as the statistical tests to identify disturbed observations are introduced for the Gauss-Helmert model. Especially, if the observations are uncorrelated, these quantities will have the same structure as in the Gauss-Markov model, where the redundancy numbers play a key role. All the derivations are based on one-dimensional and additive observation errors respectively offsets which are modeled as additional parameters to be estimated. The formulas to compute these additional parameters with the corresponding variances are also derived in this contribution. The numerical examples of plane fitting and yaw computation show, that the MDB is also in the GHM an appropriate measure to analyze the ability of an implemented least-squares algorithm to detect if outliers are present. Two sources negatively influencing detectability are identified: columns close to the zero vector in the observation matrix B and sub-optimal configuration in the design matrix A. Even if these issues can be excluded, it can be difficult to identify the correct observation as being erroneous. Therefore, the correlation coefficients between two test values are derived and analyzed. Together with the MDB these correlation coefficients are an useful tool to assess the inner reliability – and therefore the detection and identification of outliers – in the Gauss-Helmert model. Numéro de notice : A2020-040 Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1515/jag-2019-0013 date de publication en ligne : 19/10/2019 En ligne : https://doi.org/10.1515/jag-2019-0013 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94511 [article]

INS/GNSS integration using recurrent fuzzy wavelet neural networks / Parisa Doostdar in GPS solutions, vol 24 n° 1 (January 2020)  

Public [article]  inGPS solutions > vol 24 n° 1 (January 2020) Titre : INS/GNSS integration using recurrent fuzzy wavelet neural networks Type de document : Article/Communication Auteurs : Parisa Doostdar, Auteur ; Jafar Keighobadi, Auteur ; Mohammad Ali Hamed, Auteur Année de publication : 2020 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Termes descripteurs IGN] classification floue [Termes descripteurs IGN] données GNSS [Termes descripteurs IGN] filtre de Kalman [Termes descripteurs IGN] GNSS-INS [Termes descripteurs IGN] interruption du signal [Termes descripteurs IGN] ondelette [Termes descripteurs IGN] réseau neuronal artificiel [Termes descripteurs IGN] réseau neuronal récurrent [Termes descripteurs IGN] vitesse [Vedettes matières IGN] Traitement de données GNSS Résumé : (Auteur) In recent years, aided navigation systems through combining inertial navigation system (INS) with global navigation satellite system (GNSS) have been widely applied to enhance the position, velocity, and attitude information of autonomous vehicles. In order to gain the accuracy of the aided INS/GNSS in GNSS gap intervals, a heuristic neural network structure based on the recurrent fuzzy wavelet neural network (RFWNN) is applicable for INS velocity and position error compensation purpose. During frequent access to GNSS data, the RFWNN should be trained as a highly precise prediction model equipped with the Kalman filter algorithm. Therefore, the INS velocity and position error data are obtainable along with the lost intervals of GNSS signals. For performance assessment of the proposed RFWNN-aided INS/GNSS, real flight test data of a small commercial unmanned aerial vehicle (UAV) were conducted. A comparison of test results shows that the proposed NN algorithm could efficiently provide high-accuracy corrections on the INS velocity and position information during GNSS outages. Numéro de notice : A2020-019 Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s10291-019-0942-z date de publication en ligne : 23/12/2019 En ligne : https://doi.org/10.1007/s10291-019-0942-z Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94458 [article]

Kalman-filter-based undifferenced cycle slip estimation in real-time precise point positioning / Pan Li in GPS solutions, vol 23 n° 4 (October 2019)  

Public [article]  inGPS solutions > vol 23 n° 4 (October 2019) Titre : Kalman-filter-based undifferenced cycle slip estimation in real-time precise point positioning Type de document : Article/Communication Auteurs : Pan Li, Auteur ; Xinyuan Jiang, Auteur ; Xiaohong Zhang, Auteur ; et al., Auteur Année de publication : 2019 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géodésie spatiale [Termes descripteurs IGN] filtre de Kalman [Termes descripteurs IGN] glissement de cycle [Termes descripteurs IGN] interruption du signal [Termes descripteurs IGN] mesurage de phase [Termes descripteurs IGN] modèle mathématique [Termes descripteurs IGN] positionnement cinématique [Termes descripteurs IGN] positionnement ponctuel précis [Termes descripteurs IGN] précision du positionnement [Termes descripteurs IGN] station GLONASS [Termes descripteurs IGN] station GPS [Termes descripteurs IGN] temps réel Résumé : (Auteur) Global navigation satellite system (GNSS) precise point positioning (PPP) requires continuous carrier-phase observations to achieve a solution of high precision. Precisely correcting cycle slips caused by signal interruptions is crucial for recovering the data continuity. Most of the existing approaches usually employ only data of one epoch after the interruption for real-time cycle slip processing. In this study, we propose to introduce and estimate cycle slip parameters together with standard PPP parameters, such as position, ionospheric delay, and ambiguities in the case that possible cycle slips are detected, using a Kalman-filter-based procedure with the undifferenced and uncombined PPP model. The integer search strategy is used to fix cycle slips. To reduce the probability of wrong integer fixing, a strict integer validation threshold is suggested. As a result, it is not easy to fix all cycle slips with only one epoch of data. Our approach can be easily extended to use multi-epoch observations to enhance the cycle slip estimation. Once the cycle slips are correctly determined, continuous PPP can be achieved instantaneously. This new approach is tested and validated with three groups of experiments using GPS and GLONASS stations operated by the International GNSS Service from DOY 1–10, 2017, and a real vehicle kinematic data. Numerous experimental results showed that the proposed method can correctly fix the cycle slips for more than 99.5% of epochs suffering from re-convergence. On average, this method takes observation information from about 1.5–2.5 epochs to fix cycle slips and realize rapid re-convergence. Consequently, positioning performance is significantly improved. Numéro de notice : A2019-334 Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s10291-019-0894-3 date de publication en ligne : 16/07/2019 En ligne : https://doi.org/10.1007/s10291-019-0894-3 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93423 [article]

Saliency-guided deep neural networks for SAR image change detection / Jie Geng in IEEE Transactions on geoscience and remote sensing, Vol 57 n° 10 (October 2019)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > Vol 57 n° 10 (October 2019) . - pp 7365 - 7377 Titre : Saliency-guided deep neural networks for SAR image change detection Type de document : Article/Communication Auteurs : Jie Geng, Auteur ; Xiaorui Ma, Auteur ; Xiaojun Zhou, Auteur ; et al., Auteur Année de publication : 2019 Article en page(s) : pp 7365 - 7377 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications [Termes descripteurs IGN] analyse d'image orientée objet [Termes descripteurs IGN] classification floue [Termes descripteurs IGN] classification non dirigée [Termes descripteurs IGN] classification par réseau neuronal [Termes descripteurs IGN] détection de changement [Termes descripteurs IGN] échantillonnage d'image [Termes descripteurs IGN] extraction de traits caractéristiques [Termes descripteurs IGN] filtre de déchatoiement [Termes descripteurs IGN] image radar moirée [Termes descripteurs IGN] logique floue [Termes descripteurs IGN] occupation du sol [Termes descripteurs IGN] saillance [Termes descripteurs IGN] télédétection en hyperfréquence Mots-clés libres : hierarchical fuzzy C-means clustering (HFCM) Résumé : (auteur) Change detection is an important task to identify land-cover changes between the acquisitions at different times. For synthetic aperture radar (SAR) images, inherent speckle noise of the images can lead to false changed points, which affects the change detection performance. Besides, the supervised classifier in change detection framework requires numerous training samples, which are generally obtained by manual labeling. In this paper, a novel unsupervised method named saliency-guided deep neural networks (SGDNNs) is proposed for SAR image change detection. In the proposed method, to weaken the influence of speckle noise, a salient region that probably belongs to the changed object is extracted from the difference image. To obtain pseudotraining samples automatically, hierarchical fuzzy C-means (HFCM) clustering is developed to select samples with higher probabilities to be changed and unchanged. Moreover, to enhance the discrimination of sample features, DNNs based on the nonnegative- and Fisher-constrained autoencoder are applied for final detection. Experimental results on five real SAR data sets demonstrate the effectiveness of the proposed approach. Numéro de notice : A2019-536 Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2019.2913095 date de publication en ligne : 19/05/2019 En ligne : http://doi.org/10.1109/TGRS.2019.2913095 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94154 [article]

An analytic expression for the phase noise of the goldstein–werner filter / Scott Hensley in IEEE Transactions on geoscience and remote sensing, vol 57 n° 9 (September 2019)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 57 n° 9 (September 2019) . - pp 6499 - 6516 Titre : An analytic expression for the phase noise of the goldstein–werner filter Type de document : Article/Communication Auteurs : Scott Hensley, Auteur Année de publication : 2019 Article en page(s) : pp 6499 - 6516 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications [Termes descripteurs IGN] bruit thermique [Termes descripteurs IGN] corrélation temporelle [Termes descripteurs IGN] densité spectrale de puissance [Termes descripteurs IGN] filtrage du bruit [Termes descripteurs IGN] filtre de Goldstein [Termes descripteurs IGN] image radar moirée [Termes descripteurs IGN] interféromètrie par radar à antenne synthétique [Termes descripteurs IGN] phase [Termes descripteurs IGN] pouvoir de résolution spectrale [Termes descripteurs IGN] rapport signal sur bruit [Termes descripteurs IGN] transformation de Fourier Résumé : (auteur) Interferogram filtering for noise reduction is a key to many radar interferometric applications. Repeat pass radar interferometry often uses data with less than ideal correlation levels resulting from either long spatial or temporal baselines or changes between observations leading to high levels of temporal correlation. To maximize the utility of such pairs filtering the interferogram to get maximal noise reduction is often needed. One technique that has proved quite useful in the geophysical community is power spectral or Goldstein–Werner filtering of the interferogram whereby a power-weighted version of the Fourier transform is used to enhance fringe visibility. Although this paper defining the filter briefly touched upon the spatial resolution and noise reduction induced by the filter, it did not provide a useful formula for predicting the phase noise after filtering. This paper derives a formula for the phase noise obtained from power spectral filtering albeit under the restriction of several simplifying assumptions to make the problem analytically tractable. In particular, it is assumed that the interferometric phase is locally well approximated by a linear phase ramp with nonlinear phase perturbations small in a spectral energy sense compared to the linear term. Numéro de notice : A2019-343 Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2019.2906549 date de publication en ligne : 25/04/2019 En ligne : http://doi.org/10.1109/TGRS.2019.2906549 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93378 [article]

Combination of GRACE monthly gravity fields on the normal equation level / Ulrich Meyer in Journal of geodesy, vol 93 n° 9 (September 2019)  

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Decomposition of geodetic time series: A combined simulated annealing algorithm and Kalman filter approach / Feng Ming in Advances in space research, vol 64 n°5 (1 September 2019)  

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Robust M–M unscented Kalman filtering for GPS/IMU navigation / Cheng Yang in Journal of geodesy, vol 93 n° 8 (August 2019)  

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Mapping the wavelength position of mineral features in hyperspectral thermal infrared data / Christoph Hecker in International journal of applied Earth observation and geoinformation, vol 79 (July 2019)  

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On the detectability of mis-modeled biases in the network-derived positioning corrections and their user impact / Amir Khodabandeh in GPS solutions, vol 23 n° 3 (July 2019)  

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Real-time sea-level monitoring using Kalman filtering of GNSS-R data / Joakim Strandberg in GPS solutions, vol 23 n° 3 (July 2019)  

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An improved robust Kalman filtering strategy for GNSS kinematic positioning considering small cycle slips / Wanke Liu in Advances in space research, vol 63 n° 9 (1 May 2019)  

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Coastline extraction from SAR images using robust ridge tracing / Dailiang Wang in Marine geodesy, vol 42 n° 3 (May 2019)  

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Real-time GPS satellite orbit and clock estimation based on OpenMP / Kaifa Kuang in Advances in space research, vol 63 n° 8 (15 April 2019)  

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BIM-Tracker: A model-based visual tracking approach for indoor localisation using a 3D building model / Debaditya Acharya in ISPRS Journal of photogrammetry and remote sensing, vol 150 (April 2019)  

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