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Statistical properties of the amplitude and phase of GPS L1 signals sampled at 50 Hz are investigated to understand the turbulent behavior of the polar region ionosphere. Wavelet detrended amplitude and phase data are used to construct the probability distribution function (PDF) of the amplitude and phase fluctuations of the signal. Turbulent behavior of the ionosphere is quantified using the skewness and kurtosis of the PDF. It is found that these two independent moments are related through a parabolic relationship, which was also reported in the case of turbulent neutral fluids and turbulent laboratory plasmas.

We present a multiscale analysis of the received amplitude fluctuations of the L1 GPS signal. The analysis consists of constructing a differential amplitude signal by taking the difference between the signal at time t and the signal at time t + τ, where τ represents a time lag. The probability density functions of the measured differential amplitude fluctuations are computed and fitted with Castaing distributions. The fourth normalized moment of the distributions is used to investigate the intermittent nature of the signal. The results reveal direct evidence that the intermittent aspect of the investigated scintillation events is more pronounced at small differential time lags than at long ones.

Using Global Navigation Satellite System observations, such as the amplitude and the phase components of the GPS L1 signal, ionospheric scintillation is characterized and quantified using indices derived from those observables. However, the background electron density of the ionosphere is not stationary, presenting a trend and a nonzero mean, and the GPS motion induces a Doppler shift that will contribute to the nonstationary aspect of the signal; hence, the multiscale nature of the diffracted signal makes it difficult to extract the components of the signal that correspond to scintillation. Constructing scintillation indices from a signal that has a nonscintillation component will lead to erroneous estimation and biased characterization of the scintillation. In this context, we present a technique aiming at retrieving the scintillation components from the raw, transionospheric radio signals. Using wavelet analysis, we define and maximize the entropy of the system, which is composed of two subsystems corresponding to scintillation and nonscintillation contributions. The Tsallis entropy has been considered for the power component, for which a non‐Gaussian behavior has been observed. This entropy is based on a nonextensive approach that introduces a parameter q, quantifying the nonextensivity. On the other hand, the phase presents a Gaussian behavior and is analyzed using the Shannon‐Gibbs entropy. In both cases, the optimum cutoff scale, delimiting the scintillation components, is estimated via the maximization of the entropy, which, as defined here, is a function of the temporal scale. This optimization of the cutoff scale will be key in the construction of an optimum, unbiased index quantifying the ionospheric scintillation using GPS signal.

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