Characterization of the ionospheric scintillations at high latitude using GPS signal
Bibliographic record
Abstract
Summary form only given. Transionospheric radio signals experience both amplitude and phase variations as a result of their propagation through a turbulent ionosphere; this phenomenon is known as ionospheric scintillations. As a result of these fluctuations, GPS receivers lose track of signals, and consequently induce position and navigational errors. Therefore, a need to study these scintillations and their causes arises in order to resolve the navigational problem, and at the same time develop analytical and numerical radio propagation models. In order to quantify and qualify the High latitude ionospheric scintillations, we analyze the probability density functions (PDFs) of L1 GPS signals at 50Hz using the Canadian High Arctic Ionospheric Network (CHAIN) measurements. The raw signal is detrended using a wavelet-based technique and the detrended power and phase of the signal are used to construct probability density functions (PDFs) of the scintillating signal. The resulting PDFs are non-Gaussian. From these PDFs higher order moments are estimated. The calculated moments of the Power and phase distribution functions will help to quantify some of the scintillation characteristics and in the process provide a base for forecasting, i.e. develop a scintillation climatology model. The profile of the skewness-kurtosis for the power fluctuation has been found to collapse to a parabolic line. This allows us to draw analogies with other plasma physics experiments and neutral fluid turbulence where such a relation has been observed. The intermittent aspect of the scintillations is investigated by estimating the probability density functions (PDFs) for different fluctuation time scales. The Kurtosis of the PDFs is used to quantify the intermittency of the amplitude and phase fluctuations. This aspect of the signal has been found to be scale dependent, and the dependence is quantified and presented. In order to characterize and model the statistical behavior of the phase and the amplitude fluctuation we proceed to a functional fit of the resulting PDFs using the Castaing distribution function. The latter is a convolution of a Gaussian function with a lognormal distribution of its variance. The resulting fits are presented, and an analysis of the moments of these distributions is discussed. In the scope of providing an estimate for an average spatial scale of the irregularities characterizing the turbulent activities within the scattering layer, we verify the validity of the Taylor hypothesis for the Ionospheric scintillation case. The calculated higher-order moments of the amplitude and phase distribution functions will help provide a base for forecasting, i.e. develop a scintillation climatology model. This statistical analysis, including power spectra, along with a numerical simulation, will constitute the backbone of a high latitude scintillation model.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".