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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)  

Public [article]  inGPS solutions > vol 27 n° 2 (April 2023) . - n° 91 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 navigation Résumé : (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 [article]

3D LiDAR aided GNSS/INS integration fault detection, localization and integrity assessment in urban canyons / Zhipeng Wang in Remote sensing, vol 14 n° 18 (September-2 2022)  

Public [article]  inRemote sensing > vol 14 n° 18 (September-2 2022) . - n° 4641 Titre : 3D LiDAR aided GNSS/INS integration fault detection, localization and integrity assessment in urban canyons Type de document : Article/Communication Auteurs : Zhipeng Wang, Auteur ; Bo Li, Auteur ; Zhiqiang Dan, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 4641 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] canyon urbain [Termes IGN] couplage GNSS-INS [Termes IGN] détection de cible [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] erreur de positionnement [Termes IGN] filtre adaptatif [Termes IGN] intégration de données [Termes IGN] intégrité des données [Termes IGN] khi carré [Termes IGN] semis de points Résumé : (auteur) The performance of Global Navigation Satellite System (GNSS) and Inertial Navigation System (INS) integrated navigation can be severely degraded in urban canyons due to the non-line-of-sight (NLOS) signals and multipath effects. Therefore, to achieve a high-precision and robust integrated system, real-time fault detection and localization algorithms are needed to ensure integrity. Currently, the residual chi-square test is used for fault detection in the positioning domain, but it has poor sensitivity when faults disappear. Three-dimensional (3D) light detection and ranging (LiDAR) has good positioning performance in complex environments. First, a LiDAR aided real-time fault detection algorithm is proposed. A test statistic is constructed by the mean deviation of the matched targets, and a dynamic threshold is constructed by a sliding window. Second, to solve the problem that measurement noise is estimated by prior modeling with a certain error, a LiDAR aided real-time measurement noise estimation based on adaptive filter localization algorithm is proposed according to the position deviations of matched targets. Finally, the integrity of the integrated system is assessed. The error bound of integrated positioning is innovatively verified with real test data. We conduct two experiments with a vehicle going through a viaduct and a floor hole, which, represent mid and deep urban canyons, respectively. The experimental results show that in terms of fault detection, the fault could be detected in mid urban canyons and the response time of fault disappearance is reduced by 70.24% in deep urban canyons. Thus, the poor sensitivity of the residual chi-square test for fault disappearance is improved. In terms of localization, the proposed algorithm is compared with the optimal fading factor adaptive filter (OFFAF) and the extended Kalman filter (EKF). The proposed algorithm is the most effective, and the Root Mean Square Error (RMSE) in the east and north is reduced by 12.98% and 35.1% in deep urban canyons. Regarding integrity assessment, the error bound can overbound the positioning errors in deep urban canyons relative to the EKF and the mean value of the error bounds is reduced. Numéro de notice : A2022-769 Affiliation des auteurs : non IGN Thématique : IMAGERIE/POSITIONNEMENT Nature : Article DOI : 10.3390/rs14184641 Date de publication en ligne : 16/09/2022 En ligne : https://doi.org/10.3390/rs14184641 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101795 [article]

Adaptive Kalman filter for real-time precise orbit determination of low earth orbit satellites based on pseudorange and epoch-differenced carrier-phase measurements / Min Li in Remote sensing, vol 14 n° 9 (May-1 2022)  

Public [article]  inRemote sensing > vol 14 n° 9 (May-1 2022) . - n° 2273 Titre : Adaptive Kalman filter for real-time precise orbit determination of low earth orbit satellites based on pseudorange and epoch-differenced carrier-phase measurements Type de document : Article/Communication Auteurs : Min Li, Auteur ; Tianhe Xu, Auteur ; Yali Shi, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 2273 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Techniques orbitales [Termes IGN] ambiguïté entière [Termes IGN] filtre adaptatif [Termes IGN] filtre de Kalman [Termes IGN] matrice de covariance [Termes IGN] mesurage de phase [Termes IGN] orbite basse [Termes IGN] orbitographie [Termes IGN] orbitographie par GNSS [Termes IGN] temps réel Résumé : (auteur) Real-time precise orbit determination (POD) of low earth orbiters (LEOs) is crucial for orbit maintenance as well as autonomous operation for space missions. The Global Positioning System (GPS) has become the dominant technique for real-time precise orbit determination (POD) of LEOs. However, the observation conditions of near-earth space are more critical than those on the ground. Real-time POD accuracy can be seriously affected when the observation environment suffers from strong space events, i.e., a heavy solar storm. In this study, we proposed a reliable adaptive Kalman filter based on pseudorange and epoch-differenced carrier-phase measurements. This approach uses the epoch-differenced carrier phase to eliminate the ambiguities and thus reduces the significant number of unknown parameters. Real calculations demonstrate that four to five observed GPS satellites is sufficient to solve reliable position parameters. Furthermore, with accurate pseudorange and epoch-differenced carrier-phase-based reference orbits, orbital dynamic disturbance can be detected precisely and reliably with an adaptive Kalman filter. Analyses of Swarm-A POD show that sub-meter level real-time orbit solutions can be obtained when the observation conditions are good. For poor observation conditions such as the GRACE-A satellite on 8 September 2017, when fewer than five GPS satellites were observed for 14% of the observation time, 1–2 m orbital accuracy can still be achieved with the proposed approach. Numéro de notice : A2022-386 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article DOI : 10.3390/rs14092273 Date de publication en ligne : 08/05/2022 En ligne : https://doi.org/10.3390/rs14092273 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100665 [article]

Real-time GNSS precise point positioning using improved robust adaptive Kalman filter / Abdelsatar Elmezayen in Survey review, Vol 53 n° 381 (November 2021)  

Public [article]  inSurvey review > Vol 53 n° 381 (November 2021) . - pp 528 - 542 Titre : Real-time GNSS precise point positioning using improved robust adaptive Kalman filter Type de document : Article/Communication Auteurs : Abdelsatar Elmezayen, Auteur ; Ahmed El-Rabbany, Auteur Année de publication : 2021 Article en page(s) : pp 528 - 542 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géodésie spatiale [Termes IGN] erreur de positionnement [Termes IGN] filtre adaptatif [Termes IGN] filtre de Kalman [Termes IGN] phase [Termes IGN] positionnement par Galileo [Termes IGN] positionnement par GNSS [Termes IGN] positionnement ponctuel précis [Termes IGN] temps réel [Termes IGN] valeur aberrante Résumé : (Auteur) Multi-constellation GNSS precise point positioning (PPP) typically uses the extended Kalman filter (EKF) for kinematic applications. Unfortunately, the obtained positioning accuracy in this approach is prone to errors caused by measurement outliers and the system’s dynamic model. An adaptive robust Kalman filter (RKF) was recently developed to mitigate these errors. However, RKF uses empirical values as detection thresholds for the outliers, which requires the measurements to be from the same constellation and of equal precision to obtain an optimal PPP solution. The classification robust adaptive Kalman filter (CAKF) has subsequently been developed to deal with measurements of different precisions, namely pseudorange and carrier-phase measurements. This paper proposes a real-time GPS/Galileo PPP system, which employs a modified version of CAKF called the Improved Robust adaptive Kalman Filter (IRKF). The positioning performance of GPS/Galileo PPP through the IRKF is initially verified in comparison with those obtained through the EKF, RKF, and CAKF using the Centre for Orbit Determination in Europe (CODE) final orbit and clock products in both of static and kinematic modes. The real-time GPS/Galileo PPP solution through the IRKF is then assessed in comparison with its near-real-time counterpart. The results indicate that when the IRKF approach is utilised, the positioning accuracy is significantly improved and the convergence behaviour is enhanced compared with results from EKF, conventional RKF, and CAKF. In the real-time mode, centimeter-level horizontal positioning accuracy is achieved under an open sky environment, while decimeter-level horizontal positioning accuracy is achieved under a challenging environment. On the other hand, decimeter-level accuracy is achieved for the vertical positioning component under all environmental scenarios. Moreover, the positioning accuracy of the real-time solution is comparable to the near-real-time counterpart. Numéro de notice : A2021-914 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/00396265.2020.1846361 Date de publication en ligne : 23/11/2020 En ligne : https://doi.org/10.1080/00396265.2020.1846361 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99317 [article]

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]

Double adaptive intensity-threshold method for uneven Lidar data to extract road markings / Chengming Ye in Photogrammetric Engineering & Remote Sensing, PERS, vol 87 n° 9 (September 2021)  

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An adaptive filtering algorithm of multilevel resolution point cloud / Youyuan Li in Survey review, Vol 53 n° 379 (July 2021)  

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A high-resolution satellite DEM filtering method assisted with building segmentation / Yihui Li in Photogrammetric Engineering & Remote Sensing, PERS, vol 87 n° 6 (June 2021)  

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Adaptive filtering / Wenping Cao (2021)  

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Mathematics and digital signal processing / Pavel Lyakhov (2021)  

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A sequential Monte Carlo framework for noise filtering in InSAR time series / Mehdi Khaki in IEEE Transactions on geoscience and remote sensing, vol 58 n° 3 (March 2020)  

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Unsupervised extraction of urban features from airborne lidar data by using self-organizing maps / Alper Sen in Survey review, vol 52 n° 371 (March 2020)  

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Reconnaissance automatique d’objets pour le jumeau numérique ferroviaire à partir d’imagerie aérienne / Valentin Desbiolles (2020)  

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Multitemporal SAR images denoising and change detection : applications to Sentinel-1 data / Weiying Zhao (2019)  

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Adaptive correlation filters with long-term and short-term memory for object tracking / Chao Ma in International journal of computer vision, vol 126 n° 8 (August 2018)  

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