Ionospheric scintillation sensitive GNSS tracking error models and mitigation approaches
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Résumé
Ionospheric scintillation refers to the rapid and random fluctuations in intensity and phase of radio frequency signals when they propagate through plasma density irregularities in the ionosphere. It is more frequently observed in the auroral to polar regions and the equatorial to low latitude regions. When scintillation occurs on Global Navigation Satellite System (GNSS), the GNSS signal quality and receiver performance can be significantly degraded, thus increasing the errors in positioning and navigation. Under strong scintillation, the GNSS receiver can even lose the lock on the signals, posing serious threats to safety-critical GNSS applications and precise positioning. \nFor a better understanding of scintillation effects on GNSS signals and receivers, as well as to mitigate the scintillation effects on GNSS positioning, research is carried out in this thesis focusing on the following three aspects: (1) characterizing the GNSS signal intensity fadings under scintillation, (2) modelling scintillation effects on GNSS receiver tracking loops and (3) developing scintillation mitigation approaches to support high accuracy GNSS positioning under scintillation. \nSignal intensity fadings is one of the reasons that degrade the GNSS receiver tracking performance. By exploiting three months of raw scintillation data recorded by an ionospheric scintillation monitoring receiver (ISMR) deployed at low latitudes, signal intensity fadings due to scintillation are detected and characterized. Their effects on receiver tracking performance are analysed, which contributes to better understanding the low latitude scintillation effects on GNSS receivers. In order to quantitatively model the scintillation effects on GNSS receiver Phase Locked Loops (PLLs) and Delayed Locked Loop (DLLs), the phase and code jitter are estimated, respectively, at the output of PLL and DLL, taking scintillation effects into consideration. The existing models to estimate the phase and code jitters are studied. To address the concerns of the existing models, an alternative approach is developed to estimate the phase and code jitter under scintillation using the output of tracking loop discriminators, which better reflects the actual PLL and DLL tracking performance under scintillation. Additionally, the distribution of the tracking errors are analysed in the presence of scintillation. A customer-defined probability density function is proposed for the first time, which successfully describes the distribution of the PLL tracking errors under different levels of scintillation. \nThe approach to mitigate scintillation effects on GNSS positioning is studied. This thesis employs a phase and code jitter weighting approach to reduce the positioning errors caused by scintillation. In this approach, the positioning stochastic models are improved using the estimated phase and code jitter values considering scintillation effects. In order to improve the performance of this approach, 1-second scintillation indices are proposed in this thesis, which shows more effectiveness in describing the signal fluctuations under scintillation compared with the widely used 1-minute scintillation indices. Additionally, the 1-second scintillation indices outperform the 1-minute ones when used in mitigating positioning errors under scintillation. To implement the scintillation mitigation approach on generic receivers, which are not able to estimate the scintillation indices and consequently the phase and code jitter, the concept of phase and code jitter maps is exploited in this thesis. In this way, generic receivers can extract and calculate the jitter values directly from these maps for each measurement. Regional phase and code jitter maps are constructed in northern Canada using the scintillation data recorded during the geomagnetic storm in September 2017. Results show that with the help of the jitter maps constructed in this thesis, the positioning accuracy at both the ISMR and generic receiver stations can be greatly improved under scintillation.
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Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,057 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle