Correlation Properties of a 2-D Array of High Latitude Scintillation Receivers
Notice bibliographique
Résumé
Short-term signal fading and rapid phase changes can occur when the Global Navigation Satellite Systems (GNSS) signals pass through regions of ionospheric irregularities of scale sizes around tens to hundreds of meters [1]. At high latitudes, phase scintillations are observed more often than amplitude scintillations and are due to a variety of physical instability mechanisms in both the E and F regions of the ionosphere. When the ionosphere is irregular, diffractive scintillations will occur. The temporal behavior of diffractive scintillations depends on the Fresnel length of the scintillations, the drift speed of the ionosphere, and the relative velocities of the satellites and receivers [2]. There have been a number of significant high latitude studies of scintillation using the Global Positioning System (GPS), e.g., [3]. Most GPS high latitude scintillation studies were made with single GPS scintillation receivers or a network with baselines of 100s of kilometers, and therefore were not able to investigate the local spatial spectrum of the irregularities or the drift speeds. Scintillation studies for arrays around km scale baselines have been developed by [4] and more recently for an array for polar scintillations [5]. We build on this previous body of work with the beginning of an in-depth study of the spatial-temporal properties of GPS scintillations in the auroral oval region using a multi-receiver array deployed near the equatorial boundary of the auroral region and the night-side transition region. In late 2012, a test array of ASTRA Connected Autonomous Space Environment Sensors (CASES) was installed around the University of Calgary. These receivers stream one minute averages of scintillation parameters (S4 and sigma_phi), as well as high-rate I and Q samples to a server. From this test array, a final 7 receiver array is deployed in Canada at a location near the equatorial auroral boundary. This array is used to study the space-time properties of ionospheric irregularities that cause scintillations, through forward modeling and inverse diffraction tomography methods. In order to make such studies, we establish a scintillation event database. The database is based upon a “quick-look” set of scintillation data across the array, choosing both non-scintillating periods as baseline cases, and scintillating periods. The criteria for events being entered into the database are: • Significant scintillation on all receivers. • All-sky imagers observe significant auroral structuring [6]. • The GPS lines of sight (LOS) pass through the spatial region of the auroral structuring. • Location of the auroral boundary with respect to the scintillating LOS is estimated. The database is then used to choose periods for more in depth study of ionospheric irregularities by analysis of the high-rate I and Q data across the array. The results of this analysis will improve our understanding of the space-time distribution of ionospheric irregularities, the large scale drivers that cause the development of irregularities, and the nowcast and forecast of scintillations for GNSS systems. This paper focuses upon initial results from the array of scintillation receivers, including estimation of drift velocities from cross-correlations, estimation of the spectrum of irregularities, and geophysical conditions that caused the scintillations. [1] Morrissey, T.N., K. W. Shallberg, A. J. Van Dierendonck, and M. J. Nicholson (2004), GPS receiver performance characterization under realistic ionospheric phase scintillation environments, Radio Sci., vol. 39, pp. 1–18. [2] Kintner, P. M., B. M. Ledvina, E. R. de Paula, and I. J. Kantor (2004), Size, shape, orientation, speed, and duration of GPS equatorial anomaly scintillations, Radio Sci., 39, RS2012, doi:10.1029/2003RS002878. [3] Skone S., M. Feng, R. Tiwari and A. Coster (2009), Characterizing ionospheric irregularities for auroral scintillations, Proceedings of the 22nd International Technical Meeting of The Satellite Division of the Institute of Navigation (ION GNSS 2009), Savannah, GA, September 2009, pp. 2551-2558. [4] Grzesiak M., and A.W. Wernik (2009), Dispersion analysis of spaced antenna scintillation measurement Ann. Geophys., 27, 2843–2849. [5] Wang, J., Morton, Y., Zhou, Q., Pelgrum, W., Spatial Characterization of High Latitude Ionosphere Scintillations, Proceedings of the 25th International Technical Meeting of The Satellite Division of the Institute of Navigation (ION GNSS 2012), Nashville, TN, September 2012, pp. -. [6] Smith, A. M., C. N. Mitchell, R. J. Watson, R. W. Meggs, P. M. Kintner, K. Kauristie, and F. Honary (2008), GPS scintillation in the high arctic associated with an auroral arc, Space Weather, 6, S03D01, doi:10.1029/2007SW000349.
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 distillée sur la base complète
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 | 0,002 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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 tête enseignante, 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 ».