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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]

An improved computerized ionospheric tomography model fusing 3-D multisource ionospheric data enabled quantifying the evolution of magnetic storm / Jian Kong in IEEE Transactions on geoscience and remote sensing, vol 59 n° 5 (May 2021)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 59 n° 5 (May 2021) . - pp 3725 - 3736 Titre : An improved computerized ionospheric tomography model fusing 3-D multisource ionospheric data enabled quantifying the evolution of magnetic storm Type de document : Article/Communication Auteurs : Jian Kong, Auteur ; Lulu Shan, Auteur ; Chen Zhou, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 3725 - 3736 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de géodésie spatiale [Termes IGN] données GNSS [Termes IGN] erreur absolue [Termes IGN] filtre de Kalman [Termes IGN] fusion de données multisource [Termes IGN] modèle ionosphérique [Termes IGN] modèle stochastique [Termes IGN] perturbation ionosphérique [Termes IGN] tempête magnétique [Termes IGN] teneur totale en électrons [Termes IGN] tomographie Résumé : (auteur) Global Navigation Satellite System (GNSS) ionospheric tomography is a typical ill-posed problem. Joint inversion with external observation data is one of the effective ways to mitigate the problem. In this article, by fusing 3-D multisource ionospheric data, and improving the stochastic model, an improved GNSS tomographic algorithm MFCIT [computerized ionospheric tomography (CIT) using mapping function] is presented. The accuracy of the algorithm is validated by selected data under different geomagnetic and solar conditions acquired in Europe. The results show that the estimated, statistically significant uncertainty for each of the layers is about 0.50–3.0TECU, with the largest absolute error within 6.0TECU. The advantage of the MFCIT is that it is based on the Kalman filter, which enables efficient near real-time 3-D monitoring of ionosphere. The temporal resolution can reach ~1 min level. Here, we apply the ionospheric tomography inversion to the magnetic storm on January 7, 2015, in the European region, and quantified the evolution of the storm. The results show that the difference of the core region between the MFCIT and CODE GIM is less than 1TECU. More importantly, during the initial phase of the storm, when the ionospheric disturbance is not evident in the single layer CODE GIM model, the MFCIT shows obvious positive disturbances in the upper ionosphere, although there is no disturbance in the F2 layer. The MFCIT further tracks the evolution of the magnetic storm that the ionospheric disturbance expands from the upper to the lower ionosphere layers, and at UT12:00, the disturbance continues to spread to the F2 layer. Numéro de notice : A2021-396 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2020.3022949 date de publication en ligne : 24/09/2020 En ligne : https://doi.org/10.1109/TGRS.2020.3022949 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97686 [article]

The Realization and evaluation of PPP ambiguity resolution with INS aiding in marine survey / Zhenqiang Du in Marine geodesy, vol 44 n° 2 (March 2021)  

Public [article]  inMarine geodesy > vol 44 n° 2 (March 2021) . - pp 136 - 156 Titre : The Realization and evaluation of PPP ambiguity resolution with INS aiding in marine survey Type de document : Article/Communication Auteurs : Zhenqiang Du, Auteur ; Hongzhou Chai, Auteur ; Guorui Xiao, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 136 - 156 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géodésie spatiale [Termes IGN] ambiguïté entière [Termes IGN] filtre de Kalman [Termes IGN] fractional cycle bias [Termes IGN] milieu marin [Termes IGN] positionnement inertiel [Termes IGN] positionnement ponctuel précis [Termes IGN] précision du positionnement [Termes IGN] qualité des données [Termes IGN] récepteur GNSS [Termes IGN] résolution d'ambiguïté [Termes IGN] trajet multiple Résumé : (auteur) The tightly coupled global navigation satellite system (GNSS) precise point positioning (PPP) and inertial navigation system (INS) can provide high-precision position, velocity and attitude information. The coupled system utilizes single receiver, which is particularly suitable for the environment without reference station, such as marine survey. In the former works, the integer ambiguity resolution of PPP/INS in terrestrial environment is researched. However, the GNSS observation is severely affected by the multipath effect in marine environment. In addition, the sideslip caused by wind and sea wave also impact float ambiguity estimation, consequently introducing difficulty for PPP ambiguity fixing. Therefore, the PPP/INS tightly coupled model with fixed ambiguity is proposed for marine survey. The correction model of INS gyroscope bias in closed-loop is deduced in detail. The influence of ship motion noise and multipath in marine environment is reduced by introducing the robust factor to the Kalman filter. The feasibility of the method is verified in a real marine experiment, with a detail evaluation of the data quality and positioning accuracy. The results show that the accuracy of PPP/INS can reach centimeter level after fixing the ambiguity in marine environment. Furthermore, the precise INS-predicted position can significantly shorten the re-fixed time of PPP/INS, which proves the efficiency of the proposed approach. Numéro de notice : A2021-267 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article DOI : 10.1080/01490419.2020.1852986 date de publication en ligne : 07/12/2020 En ligne : https://doi.org/10.1080/01490419.2020.1852986 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97321 [article]

Space-time disease mapping by combining Bayesian maximum entropy and Kalman filter: the BME-Kalman approach / Bisong Hu in International journal of geographical information science IJGIS, vol 35 n° 3 (March 2021)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 35 n° 3 (March 2021) . - pp 466 - 489 Titre : Space-time disease mapping by combining Bayesian maximum entropy and Kalman filter: the BME-Kalman approach Type de document : Article/Communication Auteurs : Bisong Hu, Auteur ; Pan Ning, Auteur ; Yi Li, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 466 - 489 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Cartographie thématique [Termes IGN] carte sanitaire [Termes IGN] Chine [Termes IGN] entropie maximale [Termes IGN] filtre de Kalman [Termes IGN] géostatistique [Termes IGN] modèle dynamique [Termes IGN] régression Résumé : (auteur) In this work, a synthesis of the Bayesian maximum entropy (BME) and the Kalman filter (KF) methods, which enhances their individual strengths and overcomes certain of their weaknesses for spatiotemporal mapping purposes, is proposed in a spatiotemporal disease mapping context. The proposed BME-Kalman synthesis allows BME to use information from both parametric regression modeling and KF estimation leading to enhanced knowledge bases. The BME-Kalman synthetic approach is used to study the space-time incidence mapping of the hand, foot and mouth disease (HFMD) in Shandong province (China) during the period May 1st, 2008 to March 19th, 2009. The results showed that the BME-Kalman approach exhibited very good regressive and predictive accuracies, maintained a very good performance even during low-incidence and extremely low-incidence periods, offered an improved description of hierarchical disease characteristics compared to traditional mapping techniques, and provided a clear explanation of the spatial stratified incidence heterogeneity at unsampled locations. The BME-Kalman approach is versatile and flexible so that it can be modified and adjusted according to the needs of the application. Numéro de notice : A2021-165 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2020.1795177 date de publication en ligne : 22/07/2021 En ligne : https://doi.org/10.1080/13658816.2020.1795177 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97098 [article]

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A highly adaptable method for GNSS cycle slip detection and repair based on Kalman filter / Xianwen Yu in Survey review, Vol 53 n° 377 (February 2021)  

Public [article]  inSurvey review > Vol 53 n° 377 (February 2021) . - pp 169 - 182 Titre : A highly adaptable method for GNSS cycle slip detection and repair based on Kalman filter Type de document : Article/Communication Auteurs : Xianwen Yu, Auteur ; Siqi Xia, Auteur Année de publication : 2021 Article en page(s) : pp 169 - 182 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] compensation Lambda [Termes IGN] détection [Termes IGN] double différence [Termes IGN] filtre de Kalman [Termes IGN] glissement de cycle [Termes IGN] phase [Vedettes matières IGN] Traitement de données GNSS Résumé : (auteur) The cycle slip detection and repair are crucial steps in the preprocessing of GNSS carrier phase observation. Currently, however, there are few cycle slip detection and repair methods that can meet the data processing needs for diverse situations. To solve this problem, a highly adaptable cycle slip detection and repair method is proposed. First, a cycle slip detection equation is established using the pseudo-range and carrier double-differenced (DD) observations; the state equation is developed based on the satellite-ground distance. Then, a Kalman filter estimation model is established by joining the two equations. Subsequently, the cycle slip can be detected and repaired. Finally, the state parameters are refined in accordance with the conditional distribution. According to the results of the example, all the simulated cycle slips are detected and repaired by the method proposed. It shows that the method can meet the data processing needs for multiple situations. Numéro de notice : A2021-195 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/00396265.2020.1756107 date de publication en ligne : 29/04/2020 En ligne : https://doi.org/10.1080/00396265.2020.1756107 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97133 [article]

Application of baseline constraint Kalman filter to BeiDou precise point positioning / Xiaoguo Guan in Survey review, vol 53 n°376 (January 2021)  

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Integrated Kalman filter of accurate ranging and tracking with wideband radar / Shaopeng Wei in IEEE Transactions on geoscience and remote sensing, Vol 58 n° 12 (December 2020)  

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Stereophotogrammetry for 2-D building deformation monitoring using Kalman Filter / J.O. Odumosu in Reports on geodesy and geoinformatics, vol 110 n° 1 (December 2020)  

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Integer-estimable GLONASS FDMA model as applied to Kalman-filter-based short- to long-baseline RTK positioning / Pengyu Hou in GPS solutions, Vol 24 n° 4 (October 2020)  

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A low-cost integrated MEMS-based INS/GPS vehicle navigation system with challenging conditions based on an optimized IT2FNN in occluded environments / Elahe S. Abdolkarimi in GPS solutions, Vol 24 n° 4 (October 2020)  

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GipsyX/RTGx, a new tool set for space geodetic operations and research / Willy I. Bertiger in Advances in space research, vol 66 n° 3 (1 August 2020)  

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Performance of BDS triple-frequency positioning based on the modified TCAR method / Yijun Tian in Survey review, vol 52 n° 374 (August 2020)  

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A robust total Kalman filter algorithm with numerical evaluation / Sida Li in Survey review, vol 52 n° 373 (July 2020)  

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Impact of temperature stabilization on the strapdown airborne gravimetry: a case study in Central Turkey / Mehmet Simav in Journal of geodesy, vol 94 n°4 (April 2020)  

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Performance of real-time undifferenced precise positioning assisted by remote IGS multi-GNSS stations / Zhiqiang Liu in GPS solutions, vol 24 n° 2 (April 2020)  

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