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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)
[article]
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 linéaireRésumé : (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
in Journal of geodesy > vol 93 n° 8 (August 2019) . - pp 1093 - 1104[article]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)
[article]
Titre : An improved robust Kalman filtering strategy for GNSS kinematic positioning considering small cycle slips Type de document : Article/Communication Auteurs : Wanke Liu, Auteur ; Jianlong Li, Auteur ; Qi Zeng, Auteur ; et al., Auteur Année de publication : 2019 Article en page(s) : pp 2724 - 2734 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géodésie spatiale
[Termes IGN] erreur absolue
[Termes IGN] erreur de positionnement
[Termes IGN] filtre de Kalman
[Termes IGN] glissement de cycle
[Termes IGN] matrice de covariance
[Termes IGN] phase
[Termes IGN] positionnement cinématique
[Termes IGN] positionnement différentiel
[Termes IGN] positionnement par GNSS
[Termes IGN] résidu
[Termes IGN] valeur aberranteRésumé : (auteur) In GNSS (Global Navigation Satellite Systems) kinematic positioning, observations will be inevitably contaminated by cycle slips and gross errors, as the complex observation environment changes rapidly. These outliers will degrade the performance of classic Kalman filtering applied in GNSS kinematic resolution and eventually, the filtering may converge slowly or even diverge and thus the precision will be degraded. Therefore, a robust Kalman filter should be applied to resist the influence of these outliers that cannot be identified in the data preprocessing stage. Based on the conventional IGG (Institute of Geodesy and Geophysics) III equivalent weight method which addresses the outliers of the zero-weight segment with the same strategy, this paper proposes an improved robust Kalman filtering strategy that detects outliers by both posterior phase residuals and standardized residuals and handles the carrier-phase observation of zero-weight segment as cycle slips. In addition, to avoid unnecessary ambiguity reinitialization caused by the detected cycle slips, only when the carrier-phase observation of the same satellite is classified in the zero-weight segment over two consecutive epochs should the ambiguity be reinitialized. Experimental results of relative positioning show that the improved method can not only mitigate the influence of unexpected outliers in the Kalman filter but also improve the fixing rate of ambiguity resolution as well as the accuracy and reliability of positioning. Numéro de notice : A2019-396 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.asr.2017.11.041 Date de publication en ligne : 08/12/2017 En ligne : https://doi.org/10.1016/j.asr.2017.11.041 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93505
in Advances in space research > vol 63 n° 9 (1 May 2019) . - pp 2724 - 2734[article]On constrained integrated total Kalman filter for integrated direct geo-referencing / Vahid Mahboub in Survey review, vol 51 n° 364 (January 2019)
[article]
Titre : On constrained integrated total Kalman filter for integrated direct geo-referencing Type de document : Article/Communication Auteurs : Vahid Mahboub, Auteur ; Mohammad Saadatseresht, Auteur ; Alireza A. Ardalan, Auteur Année de publication : 2019 Article en page(s) : pp 26 - 34 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement du signal
[Termes IGN] filtrage du bruit
[Termes IGN] filtre de Kalman
[Termes IGN] géoréférencement direct
[Termes IGN] GPS-INS
[Termes IGN] invariant
[Termes IGN] matrice de covariance
[Termes IGN] modèle dynamiqueRésumé : (Auteur) A constrained integrated total Kalman filter algorithm is developed. It considers a quadratic constraint which may appear in some problems of integrated direct geo-referencing in particular when INS data is used as system equations of a Kalman filter algorithm. In such a case one encounters with a dynamic errors-in-variables (DEIV) model for system equations, although DEIV model has been already considered for equations of the Kalman filter algorithm and a solution namely integrated total Kalman filter (ITKF) has been given to it. Also this algorithm can be simplified to unconstraint case which is useful for some problems. It considers DEIV model for both observation equations and system equations of the Kalman filter algorithm. The predicted residuals for all variables including the random noise at the first epoch, the observational noise, the random system noise and the corresponding noise of two coefficient matrixes (in the system equations and the observation equations) besides the variance matrix of the unknown parameters are obtained. In two numerical examples, integrated direct geo-referencing problem is solved for a GPS-INS system. Numéro de notice : A2019-186 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/00396265.2017.1341736 Date de publication en ligne : 30/06/2017 En ligne : https://doi.org/10.1080/00396265.2017.1341736 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=92617
in Survey review > vol 51 n° 364 (January 2019) . - pp 26 - 34[article]Validating and comparing GNSS antenna calibrations / Ulla Kallio in Journal of geodesy, vol 93 n° 1 (January 2019)
[article]
Titre : Validating and comparing GNSS antenna calibrations Type de document : Article/Communication Auteurs : Ulla Kallio, Auteur ; Hannu Koivula, Auteur ; Sonja Lahtinen, Auteur ; Ville Nikkonen, Auteur ; Markku Poutanen, Auteur Année de publication : 2019 Article en page(s) : pp 1 - 18 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géodésie spatiale
[Termes IGN] antenne GNSS
[Termes IGN] centre de phase
[Termes IGN] erreur systématique
[Termes IGN] étalonnage d'instrument
[Termes IGN] matrice de covariance
[Termes IGN] Metsähovi
[Termes IGN] modèle mathématique
[Termes IGN] positionnement cinématique
[Termes IGN] précision millimétrique
[Termes IGN] résidu
[Termes IGN] test de performanceRésumé : (auteur) GNSS antennas have no fixed electrical reference point. The variation of the phase centre is modelled and tabulated in antenna calibration tables, which include the offset vector (PCO) and phase centre variation (PCV) for each frequency according to the elevations and azimuths of the incoming signal. Used together, PCV and PCO reduce the phase observations to the antenna reference point. The remaining biases, called the residual offsets, can be revealed by circulating and rotating the antennas on pillars. The residual offsets are estimated as additional parameters when combining the daily GNSS network solutions with full covariance matrix. We present a procedure for validating the antenna calibration tables. The dedicated test field, called Revolver, was constructed at Metsähovi. We used the procedure to validate the calibration tables of 17 antennas. Tables from the IGS and three different calibration institutions were used. The tests show that we were able to separate the residual offsets at the millimetre level. We also investigated the influence of the calibration tables from the different institutions on site coordinates by performing kinematic double-difference baseline processing of the data from one site with different antenna tables. We found small but significant differences between the tables. Numéro de notice : A2019-031 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s00190-018-1134-2 Date de publication en ligne : 22/03/2019 En ligne : https://doi.org/10.1007/s00190-018-1134-2 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=91968
in Journal of geodesy > vol 93 n° 1 (January 2019) . - pp 1 - 18[article]Atmospheric artifacts correction with a covariance-weighted linear model over mountainous regions / Zhongbo Hu in IEEE Transactions on geoscience and remote sensing, vol 56 n° 12 (December 2018)
[article]
Titre : Atmospheric artifacts correction with a covariance-weighted linear model over mountainous regions Type de document : Article/Communication Auteurs : Zhongbo Hu, Auteur ; Hongdong Fan, Auteur ; Jordi J. Mallorquí, Auteur Année de publication : 2018 Article en page(s) : pp 6995 - 70008 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications
[Termes IGN] correction atmosphérique
[Termes IGN] image Sentinel-SAR
[Termes IGN] interferométrie différentielle
[Termes IGN] interféromètrie par radar à antenne synthétique
[Termes IGN] matrice de covariance
[Termes IGN] modèle linéaire
[Termes IGN] montagne
[Termes IGN] retard troposphérique
[Termes IGN] Tenerife
[Termes IGN] variogrammeRésumé : (auteur) Mitigating the atmospheric phase delay is one of the largest challenges faced by the differential synthetic aperture radar (SAR) interferometry community. Recently, many publications have studied correcting the stratified tropospheric phase delay by assuming a linear model between them and the topography. However, most of these studies have not considered the effect of turbulent atmospheric artifacts when adjusting the linear model to data. In this paper, we present an improved technique that minimizes the influence of the turbulent atmosphere in the model adjustment. In the proposed algorithm, the model is adjusted to the phase differences of pixels instead of using the unwrapped phase of each pixel. In addition, the different phase differences are weighted as a function of its atmospheric phase screen covariance estimated from an empirical variogram to reduce, in the model adjustment, the impact of pixel pairs with a significant turbulent atmosphere. The good performance of the proposed method has been validated with both the simulated and real Sentinel-1A SAR data in the mountainous area of Tenerife island, Spain. Numéro de notice : A2018- 553 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2018.2846885 Date de publication en ligne : 17/07/2018 En ligne : http://dx.doi.org/ 10.1109/TGRS.2018.2846885 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=91652
in IEEE Transactions on geoscience and remote sensing > vol 56 n° 12 (December 2018) . - pp 6995 - 70008[article]Remote sensing scene classification using multilayer stacked covariance pooling / Nanjun He in IEEE Transactions on geoscience and remote sensing, vol 56 n° 12 (December 2018)PermalinkTowards operational marker-free registration of terrestrial lidar data in forests / Jean-François Tremblay in ISPRS Journal of photogrammetry and remote sensing, vol 146 (December 2018)PermalinkLeast-squares cross-wavelet analysis and its applications in geophysical time series / Ebrahim Ghaderpour in Journal of geodesy, vol 92 n° 10 (October 2018)PermalinkUnmixing polarimetric radar images based on land cover type identified by higher resolution optical data before target decomposition: application to forest and bare soil / Sébastien Giordano in IEEE Transactions on geoscience and remote sensing, vol 56 n° 10 (October 2018)PermalinkA methodology for least-squares local quasi-geoid modelling using a noisy satellite-only gravity field model / R. Klees in Journal of geodesy, vol 92 n° 4 (April 2018)PermalinkBayesian statistics and Monte Carlo methods / Karl Rudolf Koch in Journal of geodetic science, vol 8 n° 1 (January 2018)PermalinkPermalinkPairwise registration of TLS point clouds using covariance descriptors and a non-cooperative game / Dawei Zai in ISPRS Journal of photogrammetry and remote sensing, vol 134 (December 2017)PermalinkUncertainty assessment in geodetic network adjustment by combining GUM and Monte-Carlo-simulations / Wolfgang Niemeier in Journal of applied geodesy, vol 11 n° 2 (June 2017)PermalinkModified residual method for the estimation of noise in hyperspectral images / Asad Mahmood in IEEE Transactions on geoscience and remote sensing, vol 55 n° 3 (March 2017)PermalinkPermalinkMultiband image fusion based on spectral unmixing / Qi Wei in IEEE Transactions on geoscience and remote sensing, vol 54 n° 12 (December 2016)PermalinkSystematic effects in laser scanning and visualization by confidence regions / Karl Rudolf Koch in Journal of applied geodesy, vol 10 n° 4 (December 2016)PermalinkA measure of average error variance of line features / Eryong Liu in Cartography and Geographic Information Science, Vol 43 n° 4 (September 2016)PermalinkTaking correlations in GPS least squares adjustments into account with a diagonal covariance matrix / Gaël Kermarrec in Journal of geodesy, vol 90 n° 9 (September 2016)PermalinkOptimization of observation plan based on the stochastic characteristics of the geodetic network / Wojciech Pachelski in Reports on geodesy and geoinformatics, vol 101 (June 2016)PermalinkRapid mapping method based on free blocks of surveys / Xianwen Yu in Journal of applied geodesy, vol 10 n° 2 (June 2016)PermalinkHigh-precision positioning of radar scatterers / Prabu Dheenathayalan in Journal of geodesy, vol 90 n° 5 (May 2016)PermalinkTime series analysis of 3D coordinates using nonstochastic observations / Hiddo Velsink in Journal of applied geodesy, vol 10 n° 1 (March 2016)PermalinkSpace–time adaptive processing and motion parameter estimation in multistatic passive radar using sparse Bayesian learning / Qisong Wu in IEEE Transactions on geoscience and remote sensing, vol 54 n° 2 (February 2016)Permalink