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Estimation of swell height using spaceborne GNSS-R data from eight CYGNSS satellites / Yanli Zheng in Remote sensing, vol 14 n° 18 (September-2 2022)  

Public [article]  inRemote sensing > vol 14 n° 18 (September-2 2022) . - n° 4640 Titre : Estimation of swell height using spaceborne GNSS-R data from eight CYGNSS satellites Type de document : Article/Communication Auteurs : Yanli Zheng, Auteur ; Fu Zheng, Auteur ; Cheng Yang, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 4640 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géodésie spatiale [Termes IGN] données GLONASS [Termes IGN] données GPS [Termes IGN] double différence [Termes IGN] latitude [Termes IGN] positionnement ponctuel précis [Termes IGN] positionnement statique [Termes IGN] retard troposphérique zénithal [Termes IGN] temps de convergence Résumé : (auteur) The orbital inclination angle of the GLONASS constellation is about 10° larger than that of GPS, Galileo, and BDS. Theoretically, the higher orbital inclination angle could provide better observation geometry in high latitude regions. A wealth of research has investigated the positioning accuracy of GLONASS and its impact on multi-GNSS, but rarely considered the contribution of the GLONASS constellation’s large orbit inclination angle. The performance of GLONASS in different latitude regions is evaluated in both stand-alone mode and integration with GPS in this paper. The performance of GPS is also presented for comparison. Three international GNSS service (IGS) networks located in high, middle, and low latitudes are selected for the current study. Multi-GNSS data between January 2021 and June 2021 are used for the assessment. The data quality check shows that the GLONASS data integrity is significantly lower than that of GPS. The constellation visibility analysis indicates that GLONASS has a much better elevation distribution than GPS in high latitude regions. Both daily double-difference network solutions and daily static Precise Point Positioning (PPP) solutions are evaluated. The statistical analysis of coordinate estimates indicates that, in high latitude regions, GLONASS has a comparable or even better accuracy than that of GPS, and GPS+GLONASS presents the best estimate accuracy; in middle latitude regions, GPS stand-alone constellation provides the best positioning accuracy; in low latitude regions, GLONASS offers the worst accuracy, but the positioning accuracy of GPS+GLONASS is better than that of GPS. The tropospheric estimates of GLONASS do not present a resemblance regional advantage as coordinate estimates, which is worse than that of GPS in all three networks. The PPP processing with combined GPS and GLONASS observations reduces the convergence time and improves the accuracy of tropospheric estimates in all three networks. Numéro de notice : A2022-770 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article DOI : 10.3390/rs14184640 Date de publication en ligne : 16/09/2022 En ligne : https://doi.org/10.3390/rs14184640 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101796 [article]

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

Public [article]  inJournal of geodesy > vol 93 n° 8 (August 2019) . - pp 1093 - 1104 Titre : Robust M–M unscented Kalman filtering for GPS/IMU navigation Type de document : Article/Communication Auteurs : Cheng Yang, Auteur ; Wenzhong Shi, Auteur ; Wu Chen, Auteur Année de publication : 2019 Article en page(s) : pp 1093 - 1104 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Navigation et positionnement [Termes IGN] coefficient de corrélation [Termes IGN] couplage GNSS-INS [Termes IGN] erreur de mesure [Termes IGN] erreur de modèle [Termes IGN] filtre de Kalman [Termes IGN] matrice de covariance [Termes IGN] méthode du maximum de vraisemblance (estimation) [Termes IGN] méthode robuste [Termes IGN] modèle non linéaire Résumé : (auteur) In this paper, a robust unscented Kalman filter (UKF) based on the generalized maximum likelihood estimation (M-estimation) is proposed to improve the robustness of the integrated navigation system of Global Navigation Satellite System and Inertial Measurement Unit. The UKF is a variation of Kalman filter by which the Jacobian matrix calculation in a nonlinear system state model is not necessary. The proposed robust M–M unscented Kalman filter (RMUKF) applies the M-estimation principle to both functional model errors and measurement errors. Hence, this robust filter attenuates the influences of disturbances in the dynamic model and of measurement outliers without linearizing the nonlinear state space model. In addition, an equivalent weight matrix, composed of the bi-factor shrink elements, is proposed in order to keep the original correlation coefficients of the predicted state unchanged. Furthermore, a nonlinear error model is used as the dynamic equation to verify the performance of the proposed RMUKF with a simulation and field test. Compared with the conventional UKF, the impacts of measurement outliers and system disturbances on the state estimation are both controlled by RMUKF. Numéro de notice : A2019-370 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s00190-018-01227-5 Date de publication en ligne : 22/01/2019 En ligne : https://doi.org/10.1007/s00190-018-01227-5 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93455 [article]