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On the second order statistics for GPS ionospheric scintillation modeling
Author(s) -
Oliveira Moraes Alison,
Paula Eurico Rodrigues,
Assis Honorato Muella Marcio Tadeu,
Perrella Waldecir João
Publication year - 2014
Publication title -
radio science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.371
H-Index - 84
eISSN - 1944-799X
pISSN - 0048-6604
DOI - 10.1002/2013rs005270
Subject(s) - interplanetary scintillation , scintillation , fading , ionosphere , nakagami distribution , amplitude , geodesy , anomaly (physics) , physics , meteorology , computational physics , statistics , mathematics , geology , geophysics , optics , detector , decoding methods , coronal mass ejection , quantum mechanics , magnetic field , solar wind , condensed matter physics
Equatorial ionospheric scintillation is a phenomenon that occurs frequently, typically during nighttime, affecting radio signals that propagate through the ionosphere. Depending on the temporal and spatial distribution, ionospheric scintillation can represent a problem in the availability and precision for the Global Navigation Satellite System's users. This work is concerned with the statistical evaluation of the amplitude ionospheric scintillation fading events, namely, level crossing rate (LCR) and average fading duration (AFD). Using α‐μ model, the LCR and AFD are validated against experimental data obtained in São José dos Campos (23.1°S; 45.8°W; dip latitude 17.3°S), Brazil, a station located near the southern crest of the ionospheric equatorial ionization anomaly. The amplitude scintillation data were collected between December 2001 and January 2002, a period of high solar flux conditions. The obtained results with the proposed model fitted quite well with the experimental data and performed better when compared to the widely used Nakagami‐ m model. Additionally, this work discusses the estimation of α and μ parameters, and the best fading coefficients found in this analysis are related to scintillation severity. Finally, for theoretical situations in which no set of experimental data are available, this work also presents parameterized equations to describe these fading statistics properly.