Auroral scintillation characteristics using 100 Hz sampling of global positioning system satellite signals
Notice bibliographique
Résumé
The study of small scale irregularities in the electron density of the ionosphere is important in the efforts of fully understanding the dynamics of the ionosphere as a whole. These small scale irregularities have adverse effects on radio signals, such as those transmitted by the Global Navigation Satellite Service (GNSS) satellites. As the signal travels through these irregularities it undergoes rapid fluctuations within the signal intensity and carrier phase, these fluctuations in the signal are known as scintillations. The study of these scintillations in GNSS signals has become a very important part of the study of the ionosphere. The Canadian High Arctic Ionospheric Network (CHAIN) has recently undergone an expansion which introduced the Septentrio PolarXs Pro GNSS receiver into eight stations in the Canadian high latitude region. Benefits of the new receiver include the ability to monitor the signal intensity and carrier phase of a GNSS satellite carrier signal at a sampling rate of 100Hz where previous receivers were only capable of rates up to 50Hz. This allows us to search for scintillation signatures at higher frequencies, which was previously impossible. This in turn will help further our understanding the generation mechanism(s) of scintillation producing irregularities. Aspects of the amplitude and phase spectra during scintillation events can be used to infer physical characteristics of the ionospheric irregularities causing the signal scintillation and generating a scintillation model. Traditionally the spectral range beyond ~15Hz of a scintillation event is considered to be noise, typically referred to as the `noise floor'. The `noise floor' is consistently seen in the signal intensity spectrum but can be less common in the carrier phase spectrum where the power law structure continues into the higher frequency range. Little work has been done regarding the nature of the `noise floor' due to lack of data availability in the higher frequency range as well a prevalent interest in the clearly dominant power law. With the access to a larger spectral range an accurate look at this `noise floor' can now be performed as well as a look at the power law seen in the high frequency range of the carrier phase spectra. Initially the `noise floor' was thought to be the noise of the carrier signal dominating the scintillation. A comparison of the `noise floor' after incrementally decreasing the amount of non scintillating signal showed little to no change, furthering the hypothesis that the noise floor could contain scintillation information. Raw GPS signal data sampled at 100 Hz using Septentrio PolarXs Pro GNSS receivers is used to calculate the power spectra using multiple methods: (1) short time Fourier transforms computed at one minute windows. The mean is taken around the peak of the scintillation with window sizes varying from two to twenty minutes. (2) Wavelet transform, and (3) alternative to the butterworth filter known as the wavelet detrending filter. Resultant spectra, using above method, is used to characterize the scintillation. Preliminary results using the short time Fourier transform method show the possibility of dominant frequencies within the ~20-35Hz range using a twenty minute windows surround the peak of the scintillation event in the signal intensity data. Performing the same analysis on events with a four minute surrounding window show similar results, with dominant frequencies sharpening near 22Hz and 33Hz. Initial results also suggest dominant frequencies near the 45Hz-50Hz range but these frequencies must be treated carefully as they are very close to the Nyquist frequency. These results in itself are completely new and never observed because of the sampling limitations. Possible reasons for these dominant frequencies are currently being investigated. All preceding results are for moderate to severe scintillation events. Weak scintillations show a larger spread of possible dominant frequencies and are filtered from the results presented above. The larger spread of dominant frequencies is hypothesized to be due to the noise of the carrier signal overtaking the weak scintillation therefore these events must be analyzed separately. Full results and its implications in the understanding of the generation mechanisms of scintillation will be discussed.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,002 |
| 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) | 0,001 | 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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».