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GNSS/INS Kalman filter integrity monitoring with uncertain time correlated error processes / Omar Garcia Crespillo (2022)
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 A multipath and thermal noise joint error characterization and exploitation for low-cost GNSS PVT estimators in urban environment / Eustachio Roberto Matera (2022)
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 TélécommunicationLangues : 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 denseIndex. 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 worksNuméro 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)
[article]
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 aéroportéRésumé : (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
in Journal of applied geodesy > vol 16 n° 1 (January 2022) . - pp 37 - 57[article]Robust GNSS carrier phase-based position and attitude estimation theory and applications / Daniel Arias Medina (2022)
Titre : Robust GNSS carrier phase-based position and attitude estimation theory and applications Type de document : Thèse/HDR Auteurs : Daniel Arias Medina, Auteur Editeur : Madrid [Espagne] : Universidad Carlos III Année de publication : 2022 Importance : 249 p. Format : 21 x 30 cm Note générale : bibliographie
A dissertation submitted by in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Computer Science and Technology, Universidad Carlos III de MadridLangues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géodésie spatiale
[Termes IGN] classification du maximum a posteriori
[Termes IGN] constellation GNSS
[Termes IGN] estimation de pose
[Termes IGN] filtrage du bruit
[Termes IGN] méthode du maximum de vraisemblance (estimation)
[Termes IGN] phase GNSS
[Termes IGN] positionnement cinématique en temps réel
[Termes IGN] résolution d'ambiguïté
[Termes IGN] signal GNSSIndex. décimale : THESE Thèses et HDR Résumé : (auteur) Navigation information is an essential element for the functioning of robotic platforms and intelligent transportation systems. Among the existing technologies, Global Navigation Satellite Systems (GNSS) have established as the cornerstone for outdoor navigation, allowing for all-weather, all-time positioning and timing at a worldwide scale. GNSS is the generic term for referring to a constellation of satellites which transmit radio signals used primarily for ranging information. Therefore, the successful operation and deployment of prospective autonomous systems is subject to our capabilities to support GNSS in the provision of robust and precise navigational estimates. GNSS signals enable two types of ranging observations: –code pseudorange, which is a measure of the time difference between the signal’s emission and reception at the satellite and receiver, respectively, scaled by the speed of light; –carrier phase pseudorange, which measures the beat of the carrier signal and the number of accumulated full carrier cycles. While code pseudoranges provides an unambiguous measure of the distance between satellites and receiver, with a dm-level precision when disregarding atmospheric delays and clock offsets, carrier phase measurements present a much higher precision, at the cost of being ambiguous by an unknown number of integer cycles, commonly denoted as ambiguities. Thus, the maximum potential of GNSS, in terms of navigational precision, can be reach by the use of carrier phase observations which, in turn, lead to complicated estimation problems. This thesis deals with the estimation theory behind the provision of carrier phase-based precise navigation for vehicles traversing scenarios with harsh signal propagation conditions. Contributions to such a broad topic are made in three directions. First, the ultimate positioning performance is addressed, by proposing lower bounds on the signal processing realized at the receiver level and for the mixed real- and integer-valued problem related to carrier phase-based positioning. Second, multi-antenna configurations are considered for the computation of a vehicle’s orientation, introducing a new model for the joint position and attitude estimation problems and proposing new deterministic and recursive estimators based on Lie Theory. Finally, the framework of robust statistics is explored to propose new solutions to code- and carrier phase-based navigation, able to deal with outlying impulsive noises. Note de contenu : Introduction
I- A signal processing approach to satellite-based navigation
II- On the position and attitude estimation in multi-antenna GNSS
III- Robust estimation for navigation in harsh environments
Conclusions and future researchNuméro de notice : 15279 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Thèse étrangère Note de thèse : PhD Thesis : Computer Science and Technology : Carlos III Madrid : 2022 Organisme de stage : German Aerospace Center DOI : sans En ligne : https://e-archivo.uc3m.es/handle/10016/35375#preview Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101116
Titre : Robust GNSS phase tracking using variational bayesian inference Titre original : Méthodes de poursuite robuste de phase pour signaux GNSS basées sur l’inférence bayésienne variationnelle Type de document : Thèse/HDR Auteurs : Fabio Fabozzi, Auteur ; Stéphanie Bidon, Auteur Editeur : Toulouse : Université de Toulouse Année de publication : 2022 Importance : 173 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 Supérieur de l’Aéronautique et de l’Espace, Spécialité Signal, Image, acoustique et optimisationLangues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement du signal
[Termes IGN] données GNSS
[Termes IGN] filtrage bayésien
[Termes IGN] filtre de Kalman
[Termes IGN] glissement de cycle
[Termes IGN] inférence statistique
[Termes IGN] méthode robuste
[Termes IGN] phase
[Termes IGN] rapport signal sur bruit
[Termes IGN] récepteur GNSS
[Termes IGN] signal GNSSIndex. décimale : THESE Thèses et HDR Résumé : (auteur) In this Ph.D. thesis, we are interested in robust carrier-phase estimation by using Variational Bayesian filtering. Carrier-phase measurement has become a fundamental task in many various engineering applications such as precise point positioning in GNSS (Global Navigation Satellite System). Unfortunately, phase measurements obtained by traditional phase tracking techniques may be strongly affected by the presence of ambiguous phase jumps, known as cycle slips. The latter may strongly impact the performance of the considered phase tracking algorithm leading to, in the worst case, a permanent loss of lock (drop-lock) of the signal. A re-acquistion process is then necessary which afflicts the tracking performance. Therefore, to address this problem, we propose a robust nonlinear filter for carrier-phase tracking based on Restricted Variational Bayes inference. This methodology gives us a closed-form and easy-to-implement expression of the estimator. First, the algorithm is developed only for slow phase dynamics (i.e., first-order loop), then, its order is augmented by estimating a state vector formed by the carrier-phase and its derivatives. The performance of the proposed algorithm is compared with that of conventional techniques such as DPLL (Digital Phase Lock Loop) and KF (Kalman Filter)-based DPLL in terms of precision of estimation (root-mean-square error) and cycle slipping occurrence (mean-time-to-first-slip and cycle slip rate). The comparison is firstly conducted using synthetic data, and then, real GNSS data into a GNSS software-defined-radio receiver. Results show that the proposed method outperforms the conventional linear filters, when the signal-to-noise ratio is low. Note de contenu : Introduction
1- Introduction to GNSS
2- DPLL and robust phase tracking techniques
3- RVB algorithm in case of slow dynamics
4- RVB algorithm in case of high-order dynamics
5- RVB algorithm using real GNSS data
ConclusionNuméro de notice : 15268 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Thèse française Note de thèse : thèse de Doctorat : Signal, Image, acoustique et optimisation : Toulouse : 2022 Organisme de stage : ISAE-ONERA SCANR DOI : sans En ligne : https://depozit.isae.fr/theses/2022/2022_Fabozzi_Fabio.pdf Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100684 Mobile mapping et PCRS / Clément Benoît in Géomatique expert, n° 136 (novembre - décembre 2021)PermalinkMulti-objective CNN-based algorithm for SAR despeckling / Sergio Vitale in IEEE Transactions on geoscience and remote sensing, vol 59 n° 11 (November 2021)PermalinkReal-time GNSS precise point positioning using improved robust adaptive Kalman filter / Abdelsatar Elmezayen in Survey review, Vol 53 n° 381 (November 2021)PermalinkImproving the accuracy of spring phenology detection by optimally smoothing satellite vegetation index time series based on local cloud frequency / Jiaqi Tian in ISPRS Journal of photogrammetry and remote sensing, vol 180 (October 2021)PermalinkThe 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)PermalinkA 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)PermalinkDeep learning-based image de-raining using discrete Fourier transformation / Prasen Kumar Sharma in The Visual Computer, vol 37 n° 8 (August 2021)PermalinkUnsupervised denoising for satellite imagery using wavelet directional cycleGAN / Shaoyang Kong in IEEE Transactions on geoscience and remote sensing, vol 59 n° 8 (August 2021)PermalinkDeep learning in denoising of micro-computed tomography images of rock samples / Mikhail Sidorenko in Computers & geosciences, vol 151 (June 2021)PermalinkAn 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)Permalink