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Detection and mitigation of GNSS spoofing via the pseudorange difference between epochs in a multicorrelator receiver / Xiangyong Shang in GPS solutions, vol 26 n° 2 (April 2022)  

Public [article]  inGPS solutions > vol 26 n° 2 (April 2022) . - n° 37 Titre : Detection and mitigation of GNSS spoofing via the pseudorange difference between epochs in a multicorrelator receiver Type de document : Article/Communication Auteurs : Xiangyong Shang, Auteur ; Fuping Sun, Auteur ; Lundong Zhang, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 37 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement du signal [Termes IGN] anti-leurrage [Termes IGN] atténuation du signal [Termes IGN] brouillage [Termes IGN] détection de leurrage [Termes IGN] détection du signal [Termes IGN] filtre de Kalman [Termes IGN] mesurage de pseudo-distance [Termes IGN] méthode du maximum de vraisemblance (estimation) [Termes IGN] qualité du signal [Termes IGN] récepteur GNSS [Termes IGN] signal GNSS Résumé : (auteur) Spoofing attacks have become an increasing threat to global navigation satellite system receivers. Existing anti-spoofing algorithms concentrate on the detection of these attacks; however, they are unable to prevent the counterfeit signal, which causes false position and timing results. Some defense techniques require the assistance of other sensors or measurement devices located at different positions. These impose many restrictions on the practical applications of anti-spoofing algorithms. In this study, the multicorrelator estimator, designed initially to prevent multipath signals, is applied to detect and mitigate spoofing. A statistic is proposed for spoofing detection based on the code phase difference between counterfeit and authentic signals. This statistic can significantly reduce the rate of false and missed alarms. Assuming there is no spoofing at the beginning, the pseudorange difference between epochs is derived for spoofing validation, allowing spoofing suppression in a single receiver. Based on this study, an estimation-validation-mitigation structure is presented. A robust extended Kalman filter is proposed to reduce gross errors in the multicorrelator measurements and improve estimation accuracy. Public-spoofing datasets recorded in real environments were used to verify the performance of different parameters. A total of 81 complex correlators were introduced in the experiments. Results show that using the proposed scheme, the position or time offsets caused by spoofing drop from 600 m to approximately 20 m, and the spoofing is mitigated considerably. The proposed method provides an effective anti-spoofing structure that requires only a single antenna and does not require additional sensors. Numéro de notice : A2022-108 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article DOI : 10.1007/s10291-022-01224-4 Date de publication en ligne : 16/01/2022 En ligne : https://doi.org/10.1007/s10291-022-01224-4 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99610 [article]

A method of vision aided GNSS positioning using semantic information in complex urban environment / Rui Zhai in Remote sensing, vol 14 n° 4 (February-2 2022)  

Public [article]  inRemote sensing > vol 14 n° 4 (February-2 2022) . - n° 869 Titre : A method of vision aided GNSS positioning using semantic information in complex urban environment Type de document : Article/Communication Auteurs : Rui Zhai, Auteur ; Yunbin Yuan, Auteur Année de publication : 2022 Article en page(s) : n° 869 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Navigation et positionnement [Termes IGN] apprentissage profond [Termes IGN] cartographie et localisation simultanées [Termes IGN] centrale inertielle [Termes IGN] filtre de Kalman [Termes IGN] GNSS assisté pour la navigation [Termes IGN] information sémantique [Termes IGN] milieu urbain [Termes IGN] positionnement cinématique en temps réel [Termes IGN] positionnement par GNSS [Termes IGN] segmentation sémantique [Termes IGN] système de numérisation mobile [Termes IGN] vision par ordinateur Résumé : (auteur) High-precision localization through multi-sensor fusion has become a popular research direction in unmanned driving. However, most previous studies have performed optimally only in open-sky conditions; therefore, high-precision localization in complex urban environments required an urgent solution. The complex urban environments employed in this study include dynamic environments, which result in limited visual localization performance, and highly occluded environments, which yield limited global navigation satellite system (GNSS) performance. In order to provide high-precision localization in these environments, we propose a vision-aided GNSS positioning method using semantic information by integrating stereo cameras and GNSS into a loosely coupled navigation system. To suppress the effect of dynamic objects on visual positioning accuracy, we propose a dynamic-simultaneous localization and mapping (Dynamic-SLAM) algorithm to extract semantic information from images using a deep learning framework. For the GPS-challenged environment, we propose a semantic-based dynamic adaptive Kalman filtering fusion (S-AKF) algorithm to develop vision aided GNSS and achieve stable and high-precision positioning. Experiments were carried out in GNSS-challenged environments using the open-source KITTI dataset to evaluate the performance of the proposed algorithm. The results indicate that the dynamic-SLAM algorithm improved the performance of the visual localization algorithm and effectively suppressed the error spread of the visual localization algorithm. Additionally, after vision was integrated, the loosely-coupled navigation system achieved continuous high-accuracy positioning in GNSS-challenged environments. Numéro de notice : A2022-167 Affiliation des auteurs : non IGN Thématique : IMAGERIE/POSITIONNEMENT Nature : Article DOI : 10.3390/rs14040869 Date de publication en ligne : 11/02/2022 En ligne : https://doi.org/10.3390/rs14040869 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99792 [article]

GNSS/INS Kalman filter integrity monitoring with uncertain time correlated error processes / Omar Garcia Crespillo (2022)  

Public 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 Sciences Langues : 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'extension Résumé : (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- Appendix Numéro 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

A multipath and thermal noise joint error characterization and exploitation for low-cost GNSS PVT estimators in urban environment / Eustachio Roberto Matera (2022)  

Public Titre : A multipath and thermal noise joint error characterization and exploitation for low-cost GNSS PVT estimators in urban environment Type de document : Thèse/HDR Auteurs : Eustachio Roberto Matera, Auteur ; Carl Milner, Directeur de thèse ; Axel Javier Garcia Pena, Directeur de thèse Editeur : Toulouse : Université de Toulouse Année de publication : 2022 Importance : 348 p. Format : 21 x 30 cm Note générale : Bibliographie Thèse en vue de l'obtention du Doctorat de l'Université de Toulouse délivré par l'Institut National Polytechnique de Toulouse en Informatique et Télécommunication Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement du signal [Termes IGN] bruit thermique [Termes IGN] correction du trajet multiple [Termes IGN] corrélation temporelle [Termes IGN] filtre de Kalman [Termes IGN] rapport signal sur bruit [Termes IGN] récepteur GNSS [Termes IGN] signal GPS [Termes IGN] trajet multiple [Termes IGN] zone urbaine dense Index. décimale : THESE Thèses et HDR Résumé : (auteur) Achieving an accurate localization is a significant challenge for low-cost GNSS devices in dense urban areas. The main limitations are encountered in the urban canyons, consisting in a reduced satellite signal availability and a positioning estimation error due to the impact of Line-of-Sight and Non Line-of-Sight multipath phenomenon. This PhD study allows to understand the impact of the multipath phenomenon on the low-cost GNSS receivers and to prove the need of accurate assessment of the multipath error model affecting the GNSS measurements, especially in urban environment. It consists in the investigation, characterization, and finally, exploitation of the multipath error components affecting the pseudorange and pseudorange-rate measurements, of a single frequency, dual constellation GNSS receiver in the urban environment, operating with GPS L1 C/A and Galileo E1 OS signals. The first goal consists in providing a set of methodologies able to identify, isolate and characterize the multipath error components from the measurements under test. However, considering that the isolation of the multipath error is a complex operation due to the superimposed effects of multipath and thermal noise, the final method consists of isolating the joint contribution of multipath and thermal noise components. The isolated multipath and thermal noise error components are firstly classified depending the corresponding received signal /0 values, and, secondly, statistically characterized by means of Probability Density Function, sample mean and sample variance. Also, the temporal and spatial correlation properties of the isolated error components are calculated by means of a methodology which estimates the temporal correlations as a function of the receiver speed. In addition, an image processing methodology based on the application of a sky-facing fish-eye camera provides the determination of an empirical /0 threshold equal to 35 dB-Hz used to qualitatively identify the Non Line- Of-Sight and Line-Of-Sight received signal reception states. The resulting errors are characterized by a nonsymmetrical, positive biased PDF for a /0 lower than 35 dBHz, while they are characterized by a symmetrical and zero-centred PDF for a /0 higher than 35 dB-Hz. Correlation times for pseudoranges are ranged from around 5s for static and very low speed dynamics to around 1s for high-speed dynamics. Correlation times for pseudorange-rates ranged from around 0.5s for static and very low speed dynamics to around 0.2s for high-speed dynamics, due to the data-rate limitations. The second goal consists in exploiting the multipath and thermal noise error models and the LOS/NLOS received signal reception state estimation in a low-complex EKF-based architecture to improve the accuracy of the PVT estimates. This is obtained by implementing some techniques based on the measurement weighting approach to take into account the statistical properties of the error under exam and by the application of a time differenced architecture design to exploit the temporal correlation properties. Positioning performance of the tested solutions surpassed the performances of a simple EKF architecture and are comparable to the performances of a uBlox M8T receiver. Note de contenu : 1- Introduction 2- GNSS architecture 3- GNSS receiver processing 4- Multipath effects on the GNSS receiver tracking performances 5- Multipath characterization methodologies 6- Multipath characterization results 7- Proposed extended Kalman Filter Algorithm 8- Conclusions and recommandations for future works Numéro de notice : 15272 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Thèse française Note de thèse : Thèse de Doctorat: en Informatique et Télécommunication : Toulouse :2022 Organisme de stage : Laboratoire de Télécommunications (TELECOM-ENAC) DOI : sans En ligne : http://www.theses.fr/2022INPT0030 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100992

Recursive Gauss-Helmert model with equality constraints applied to the efficient system calibration of a 3D laser scanner / Sören Vogel in Journal of applied geodesy, vol 16 n° 1 (January 2022)  

Public [article]  inJournal of applied geodesy > vol 16 n° 1 (January 2022) . - pp 37 - 57 Titre : Recursive Gauss-Helmert model with equality constraints applied to the efficient system calibration of a 3D laser scanner Type de document : Article/Communication Auteurs : Sören Vogel, Auteur ; Dominik Ernst, Auteur ; Ingo Neumann, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 37 - 57 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Acquisition d'image(s) et de donnée(s) [Termes IGN] contrainte d'intégrité [Termes IGN] étalonnage d'instrument [Termes IGN] filtre de Kalman [Termes IGN] géoréférencement [Termes IGN] modèle de Gauss-Helmert [Termes IGN] positionnement cinématique [Termes IGN] processeur graphique [Termes IGN] télémètre laser aéroporté Résumé : (auteur) Sensors for environmental perception are nowadays applied in numerous vehicles and are expected to be used in even higher quantities for future autonomous driving. This leads to an increasing amount of observation data that must be processed reliably and accurately very quickly. For this purpose, recursive approaches are particularly suitable in terms of their efficiency when powerful CPUs and GPUs are uneconomical, too large, or too heavy for certain applications. If explicit functional relationships between the available observations and the requested parameters are used to process and adjust the observation data, complementary approaches exist. The situation is different for implicit relationships, which could not be considered recursively for a long time but only in the context of batch adjustments. In this contribution, a recursive Gauss-Helmert model is presented that can handle explicit and implicit equations and thus allows high flexibility. This recursive estimator is based on a Kalman filter for implicit measurement equations, which has already been used for georeferencing kinematic multi-sensor systems (MSS) in urban environments. Furthermore, different methods for introducing additional information using constraints and the resulting added value are shown. Practical application of the methodology is given by an example for the calibration of a laser scanner for a MSS. Numéro de notice : A2022-053 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1515/jag-2021-0026 Date de publication en ligne : 15/10/2021 En ligne : https://doi.org/10.1515/jag-2021-0026 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99448 [article]

Robust GNSS phase tracking using variational bayesian inference / Fabio Fabozzi (2022)  

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Mobile mapping et PCRS / Clément Benoît in Géomatique expert, n° 136 (novembre - décembre 2021)

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

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The integration of GPS/BDS real-time kinematic positioning and visual–inertial odometry based on smartphones / Zun Niu in ISPRS International journal of geo-information, vol 10 n° 10 (October 2021)  

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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)  

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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)  

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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)  

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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)  

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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)  

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Adaptive filtering / Wenping Cao (2021)  

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