Dynamic analysis of the polar ionosphere using the GPS signal: Toward an optimization of the cutoff scale

Abstract

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.

A Comparative Study of Spacecraft Charging Onset at Geosynchronous Altitudes: A Nonextensive Particle Approach

“…However, Chernyshov et al (2015) have first considered q ‐statistics to model the Earth's auroral region and analyzed observations for bright auroras when q ‐parameter strongly deviates from unity. Recently, dynamical analyses have also been made for polar ionosphere (Mezaoui et al, 2017) using non‐Gaussian GPS signals to show a cutoff scale with Tsallis entropy technique.…”

Performance Analysis of FFH/MFSK Using Division Combining Receiver in GPS System

“…In this paper the transmission characteristic of the proposed FFH/MFSK receiver in the GPS system named division combining receiver [1,2] is analyzed. According to the signal transition environment of GPS channel, the performance is analyzed with multiple hops per data bit under the fading channel [3,4] with partial band noise jamming (PBNJ) and AWGN.…”