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Investigation into the nonlinear Kalman filter to correct the INS/GNSS integrated navigation system / Konstantin Neusypin in GPS solutions, vol 27 n° 2 (April 2023)
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Titre : Investigation into the nonlinear Kalman filter to correct the INS/GNSS integrated navigation system Type de document : Article/Communication Auteurs : Konstantin Neusypin, Auteur ; Andrey Kupriyanov, Auteur ; Andrey Maslennikov, Auteur ; et al., Auteur Année de publication : 2023 Article en page(s) : n° 91 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Navigation et positionnement
[Termes IGN] couplage GNSS-INS
[Termes IGN] filtrage non linéaire
[Termes IGN] filtre adaptatif
[Termes IGN] filtre de Kalman
[Termes IGN] modèle d'erreur
[Termes IGN] positionnement cinématique en temps réel
[Termes IGN] système de navigationRésumé : (auteur) The integrated navigation system is the inertial navigation system (INS), corrected by global navigation satellite system (GNSS) data. The correction could be done algorithmically by utilizing nonlinear Kalman filtering (NKF). In practice, the NKF uses an INS error model as an a priori model that is not always adequate to handle the dynamics of the true and unknown INS error model. To eliminate such modeling errors, we propose a new INS/GPS correction approach with modified adaptive NKF. In the proposed NKF, instead of the a priori model, the model constructed during the pre-flight test for a particular INS is used. To realize this, the full algorithm includes an INS error model construction algorithm, a way of reduced measurement generation, and criteria for divergence detection. INS error model construction both during pre-flight test and during flight is done by the group method of data handling (GMDH). Flight experiments were performed for an empirical study of the INS error model and its effect on the total accuracy of computed navigational data. The navigational equipment was installed on the balloon—an airborne radio-transparent object. The results of the experiments validate the effectiveness and accuracy of the proposed INS/GPS correction approach. Numéro de notice : A2022-182 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article DOI : 10.1007/s10291-023-01433-5 Date de publication en ligne : 21/03/2023 En ligne : https://doi.org/10.1007/s10291-023-01433-5 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102951
in GPS solutions > vol 27 n° 2 (April 2023) . - n° 91[article]GNSS/INS Kalman filter integrity monitoring with uncertain time correlated error processes / Omar Garcia Crespillo (2022)
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Titre : GNSS/INS Kalman filter integrity monitoring with uncertain time correlated error processes Type de document : Thèse/HDR Auteurs : Omar Garcia Crespillo, Auteur ; Jan Skaloud, Directeur de thèse ; Michael Meurer, Directeur de thèse Editeur : Lausanne : Ecole Polytechnique Fédérale de Lausanne EPFL Année de publication : 2022 Importance : 180 p. Format : 21 x 30 cm Note générale : bibliographie
Thèse présentée pour l'obtention du grade de Docteur ès SciencesLangues : Anglais (eng) Descripteur : [Vedettes matières IGN] Navigation et positionnement
[Termes IGN] corrélation temporelle
[Termes IGN] couplage GNSS-INS
[Termes IGN] filtre de Kalman
[Termes IGN] fréquence multiple
[Termes IGN] modèle d'erreur
[Termes IGN] modèle de Gauss-Markov
[Termes IGN] navigation inertielle
[Termes IGN] norme
[Termes IGN] positionnement par GNSS
[Termes IGN] Receiver Autonomous Integrity Monitoring
[Termes IGN] système d'extensionRésumé : (auteur) Safety-critical navigation applications require that estimation errors be reliably quantified and bounded. Over the last decade, significant effort has been put to guarantee a bounded position estimation by using Global Navigation Satellite Systems (GNSS) by means of satellite-based or ground-based augmentation systems (SBAS, GBAS) and Advanced Receiver Autonomous Integrity Monitoring (ARAIM) for aviation. This has been achieved by carefully designing models that overbound the different residual error components in range measurements (e.g., satellite clock and orbit, tropospheric and multipath among others). On the other hand, and as part of Aircraft based Augmentation Systems (ABAS), the use of Inertial Reference Systems (IRS) has been traditionally included as additional source of redundant navigation information. More recently, the use of Inertial Navigation Systems (INS) with a wider spectrum of possible inertial sensor qualities in tighter integration with single-frequency GNSS has seen its way in a new Minimum Operational Performance Standard (MOPS). New GNSS/INS systems and standards could still benefit from the methodologies and aspects developed for future dual-frequency/multiconstellation GNSS standards. However, safety-related GNSS systems like ARAIM are snapshot-based, that is, the position estimation is performed independently at every epoch, whereas GNSS/INS systems are typically based on Kalman filtering (KF).
Therefore, the existing error overbounding models and methodologies are not enough to produce a robust KF position estimation since the impact of time-correlation in measurements must also be accounted for. Moreover, it has been observed that the time-correlation of different GNSS errors presents also some level of uncertain behavior, which makes very challenging for linear dynamic systems to produce a guaranteed solution. As proposed by GNSS Minimum Operational Performance Standards (MOPS), there are sources of time-correlated errors that can be well modelled using a first order Gauss-Markov process (GMP). Using this GMP parametric model, it is possible to capture the uncertain timecorrelated nature of error processes by allowing the variance and time correlation constant of the GMP model to be in a bounded range. Under this situation, the first part of this thesis studies the propagation of the uncertain models through the Kalman filter estimation and provides new theoretical tools in time and frequency domain to bound the KF error estimation covariance. As a result, tight stationary bounding models on the GMP uncertain processes are derived in both continuous and discrete time domain. This is extended to non-stationary models that provide tighter error bounding during an initial transient phase when measurements are first introduced (which will be relevant in scenarios with changing number of visible satellites). The new models can very easily be used during the KF implementation which might be very attractive by regulators and designers. In the second part of the thesis, the new overbounding GMP models are applied for a dual-frequency GPS-Galileo tightly-coupled GNSS/INS integration. The design of the filter and of error models is performed following compatibility with current aviation standards and ARAIM Working Group C results. The impact of the use of the new models is analysed in terms of conservativeness, integrity and continuity based on realistic operational simulations linked to airport runways. The benefit of an overbounded GNSS/INS solution is also compared with the current baseline ARAIM algorithm solution. This thesis supports the evolution of safe GNSS-based positioning systems from only snapshot based to filtered solutions. Ensuring integrity for Kalman filter in general and for GNSS/INS systems in particular is a game changer to achieve higher performance levels for future dualfrequency multi-constellation aviation services and is of vital importance for new ground and air applications like autonomous vehicles or urban air mobility.Note de contenu : Introduction
1- Preliminaries
2- Bounding Kalman Filter with uncertain error processes
3- Application to GNSS/INS integraty monitoring
4- Closing
5- AppendixNuméro de notice : 28688 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Thèse étrangère Note de thèse : Thèse de Doctorat : Sciences : Lausanne : 2022 DOI : sans En ligne : https://infoscience.epfl.ch/record/292087?ln=fr Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100103 Orbit error removal in InSAR/MTInSAR with a patch-based polynomial model / Yanan Du in International journal of applied Earth observation and geoinformation, vol 102 (October 2021)
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Titre : Orbit error removal in InSAR/MTInSAR with a patch-based polynomial model Type de document : Article/Communication Auteurs : Yanan Du, Auteur ; Hai Qiang Fu, Auteur ; Lin Liu, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : n° 102438 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications
[Termes IGN] image ALOS-PALSAR
[Termes IGN] image radar moirée
[Termes IGN] image Sentinel-SAR
[Termes IGN] interferométrie différentielle
[Termes IGN] jeu de données
[Termes IGN] modèle d'erreur
[Termes IGN] orbitographie
[Termes IGN] transformation polynomialeRésumé : (auteur) The orbit error caused by the inaccuracy of the orbit state vector can lead to fringes in differential interferograms, which can impede the estimation of deformation in differential SAR interferometry (DInSAR) applications. Usually, a set of polynomial coefficients for an entire SAR image is obtained for orbit error removal. However, the orbit error plane is influenced by overfitting in the case that the SAR satellites do not have a precise orbit. In this paper, a patch-based polynomial method is proposed to fit the orbit error plane. The new method divides an SAR image into several overlapping patches in the azimuth and range directions. Every patch obtains its own polynomial coefficients, and an iterative least-square method is used to mosaic the orbit plane. This method is tested and validated via a simulated dataset and then applied to ALOS1/2 PALSAR and Sentinel-1A datasets. The accuracy of deformation is evaluated by in situ GPS datasets. The results show that the patch-based method can fit the orbit phase plane more accurately than the traditional polynomial model with millimeter-level displacement improvement, especially in the margin areas of ALOS1/2 and for the wide-coverage Sentinel-1A datasets. Moreover, in the MTInSAR parameter calculations, the new method improves the accuracy of mean velocity calculations for ALOS1 time series, with a reduction of RMSE from 4.47 mm/yr to 3.17 mm/yr. Additionally, the new method reduces the spatial correlation of the residual topographic phase, with a mean value reduction from 0.32 m to 0.13 m. Numéro de notice : A2021-687 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1016/j.jag.2021.102438 En ligne : https://doi.org/10.1016/j.jag.2021.102438 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98419
in International journal of applied Earth observation and geoinformation > vol 102 (October 2021) . - n° 102438[article]Visualization of GNSS multipath effects and its potential application in IGS data processing / Weiming Tang in Journal of geodesy, vol 95 n° 9 (September 2021)
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Titre : Visualization of GNSS multipath effects and its potential application in IGS data processing Type de document : Article/Communication Auteurs : Weiming Tang, Auteur ; Yawei Wang, Auteur ; Xuan Zou, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : n° 103 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] grille
[Termes IGN] interférence
[Termes IGN] international GPS service for geodynamics
[Termes IGN] modèle d'erreur
[Termes IGN] phase
[Termes IGN] positionnement cinématique
[Termes IGN] qualité des données
[Termes IGN] trajet multiple
[Vedettes matières IGN] Traitement de données GNSSRésumé : (auteur) A modified multipath error mitigation method using the multi-point hemispherical grid model (MHGM) is proposed, and the influence of changes in the observation environments of IGS stations on their data quality is evaluated. The multipath error models of different satellite pairs for different observation periods can be established using the integrated multi-GNSS data in the proposed method. The test under deliberate high multipath environment reveals that this method can effectively estimate the GNSS multipath error, detect and present the orientation of the interference sources around the station. The RMS of residuals and the kinematic positioning accuracy on day 237 of 2018 are improved by 68% and 61%, respectively. Compared with the empirical site model (ESM), which can also visualize the effects of the multipath, the RMS of residuals when applying the MHGM is improved by 20%. The test with IGS historical observations shows that MHGM can effectively reflect the influence of changing multipath interference around stations on carrier phase observations, with an average improvement of 25% in the RMS of carrier phase residuals in the extrapolated 9-day validations over the past 18 years. The results of a kinematic positioning experiment in 2019 generally coincide with the RMS statistic results of carrier phase residuals as well. The MHGM demonstrates distinct potential in the influence evaluation of changes for the multipath interference around the stations on their observation quality. Numéro de notice : A2021-625 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s00190-021-01559-9 Date de publication en ligne : 28/08/2021 En ligne : https://doi.org/10.1007/s00190-021-01559-9 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98249
in Journal of geodesy > vol 95 n° 9 (September 2021) . - n° 103[article]An advanced residual error model for tropospheric delay estimation / Szabolcs Rózsa in GPS solutions, Vol 24 n° 4 (October 2020)
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Titre : An advanced residual error model for tropospheric delay estimation Type de document : Article/Communication Auteurs : Szabolcs Rózsa, Auteur ; Bence Ambrus, Auteur ; Ildiko Juni, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : 15 p. Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géodésie spatiale
[Termes IGN] erreur de positionnement
[Termes IGN] modèle d'erreur
[Termes IGN] modèle météorologique
[Termes IGN] perturbation ionosphérique
[Termes IGN] résidu
[Termes IGN] retard troposphérique
[Termes IGN] série temporelleRésumé : (auteur) Global navigation satellite systems (GNSS) are widely used for safety-of-life positioning applications. Such applications require high integrity, availability, and continuity of the positioning service. Integrity is assessed by the definition of a protection level, which is an estimation of the maximum positioning error at extremely low probability levels. The emergence of multi-frequency civilian signals and the availability of satellite-based augmentation systems improve the modeling of ionospheric disturbances considerably. As a result, in many applications the tropospheric delay tends to become one of the limiting factors of positioning—especially at low elevation angles. The currently adopted integrity concepts employ a global constant to model the variance of the residual tropospheric delay error. We introduce a new approach to derive residual tropospheric delay error models using the extreme value analysis technique. Seventeen years of global numerical weather model fields are analyzed, and new residual error models are derived for some recently developed tropospheric delay models. Our approach provides models that consider both the geographical location and the seasonal variation of meteorological parameters. Our models are validated with a 17-year-long time series of zenith tropospheric delay estimates as provided by the International GNSS Service. The results show that the developed models are still conservative, while the maximal residual error of the tropospheric delay is still improved by 39–55%. This improvement yields higher service availability and continuity in safety-of-life applications of GNSS. Numéro de notice : A2020-522 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s10291-020-01017-7 Date de publication en ligne : 07/08/2020 En ligne : https://doi.org/10.1007/s10291-020-01017-7 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95695
in GPS solutions > Vol 24 n° 4 (October 2020) . - 15 p.[article]A robust total Kalman filter algorithm with numerical evaluation / Sida Li in Survey review, vol 52 n° 373 (July 2020)
PermalinkProgress towards a rigorous error propagation for total least-squares estimates / Burkhard Schaffrin in Journal of applied geodesy, vol 14 n° 2 (April 2020)
PermalinkHow far can we trust forestry estimates from low-density LiDAR acquisitions? The Cutfoot Sioux experimental forest (MN, USA) case study / Enrico Borgogno Mondino in International Journal of Remote Sensing IJRS, vol 41 n° 12 (20 - 30 March 2020)
PermalinkEstimation of variance and spatial correlation width for fine-scale measurement error in digital elevation model / Mikhail L. Uss in IEEE Transactions on geoscience and remote sensing, vol 58 n° 3 (March 2020)
PermalinkAssessment of inner reliability in the Gauss-Helmert model / Andreas Ettlinger in Journal of applied geodesy, vol 14 n° 1 (January 2020)
PermalinkA learning approach to evaluate the quality of 3D city models / Oussama Ennafii in Photogrammetric Engineering & Remote Sensing, PERS, vol 85 n° 12 (December 2019)
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PermalinkGPS/BDS short-term ISB modelling and prediction / Nan Jiang in GPS solutions, vol 21 n° 1 (January 2017)
PermalinkTélédétection pour l'observation des surfaces continentales, Volume 2. Observation des surfaces continentales par télédétection micro-onde / Nicolas Baghdadi (2017)
PermalinkReal time monitoring ground motion using GPS with real time corrections / R. Tu in Survey review, vol 48 n° 347 (March 2016)
PermalinkAnalysis of star camera errors in GRACE data and their impact on monthly gravity field models / Pedro Inácio in Journal of geodesy, vol 89 n° 6 (June 2015)
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