After sunset, in the equatorial regions ionospheric plasma irregularities are generated due to the generalized Rayleigh‐Taylor instability. Under favorable conditions these irregularities develop in the equatorial region while mapping along the magnetic field lines giving rise to large plasma depletion structures called Equatorial Plasma Bubbles with embedded smaller structures on their walls. The global navigation satellite system (GNSS) L1 band frequency is sensitive to irregularities of the size of 300–400 m in the first Fresnel zone, which cause scattering and diffraction of the signal and produce amplitude and/or phase scintillation. Severe scintillation of GNSS signals can in turn cause loss of lock of the receiver code and/or carrier loops. As a result, GNSS navigation and positioning solution can be adversely affected by the ionospheric scintillation. There are multiple GNSS receivers designed to monitor scintillations. These receivers are based on different hardware designs and use different methodologies to process the raw data. When using simultaneous data from different GNSS scintillation monitors it is important to evaluate and compare their performances under similar scintillation conditions. The scintillation monitoring techniques may be useful for many applications that use GNSS signal. The aim of this work is to evaluate the performance of six different GNSS receivers located at São José dos Campos (23.1°S, 45.8°W, dip latitude 17.3°S) during moderate and strong scintillation activity. The amplitude (S₄) and phase (σ_ϕ) scintillation indexes from these receivers were analyzed and compared for the nights February 20–21 and November 27–28, 2013.

Ionospheric scintillation disturbs radio frequency signals affecting navigation based on Global Navigation System (GNSS), especially in Brazil, due to the large magnetic declination. The generation of real-time scintillation maps is an important way to provide scintillation monitoring. This work considers amplitude scintillation, given by the S4 index. Some existing and some proposed approaches for generating these maps are presented and tested, being each one a combination of an interpolation method with some existing and/or proposed sets of pre-processing options. These approaches are named after the related interpolation method as GRIDDATA, Inverse Distance Weighting, Radial Basis Functions and Gaussian Process Regression. The making of scintillation maps requires the interpolation of Ionospheric Pierce Point (IPP) samples, given by the S4 values for each IPP of each satellite-station link considering the set of GNSS stations of the given area and time interval. Some intervals of time that presented strong scintillation over Brazil were selected and the corresponding sets of IPP samples were used to obtain sequences of maps using all possible combinations of interpolation and pre-processing options. Furthermore, a fifth, more recent, approach was also included in the comparison. The quality of the resulting maps was assessed, concluding that the Gaussian Process Regression approach, with a specific set of pre-processing options, allows to generate the most accurate scintillation maps. The proposed map generation approach is part of a broader proposal being implemented to provide real-time scintillation maps covering the Brazilian territory.

Ionospheric scintillation affects GNSS signals that provide many essential services, making the monitoring of scintillation an important issue. This work presents a system for the real-time acquisition, generation and online dissemination of the S4 scintillation index maps covering Brazil using data from two major networks of GNSS monitoring stations, LISN and INCT. The maps are made using an innovative pre-processing and interpolation scheme. The system is already implemented and tested, being composed of a single real-time server with a database and modules that perform reception from the GNSS stations, data processing, and the online dissemination. All these tasks are executed asynchronously in a pipeline manner using the database as a central hub without any loss of data. The challenges that must be overcome to have real-time capability were: (i) to configure GNSS stations to send S4 data to a real-time server able to (ii) receive S4 data from the GNSS stations, (iii) generate sequences of S4 scintillation maps, and (iv) make these maps available in a web server. The implemented system was able to acquire data from all available stations of the monitoring networks, being robust concerning interruption of connections or different processing times of the tasks.

Total Electron Content (TEC) allows to evaluate the state of the ionosphere. Radio waves like GNSS signals traversing the ionosphere suffer delays and refraction. Ionospheric plasma irregularities may be generated in the equatorial regions after sunset and extend to low latitudes forming large plasma depleted regions named ionospheric bubbles. Signature of these bubbles can be observed at TEC maps. Inside plasma bubbles smaller scale size irregularities are generated causing scintillation in GNSS signals. This work compared TEC maps from some sources, with different temporal and spatial resolutions/coverage. Significant differences were found. For each source, there are differences in the treatment and preprocessing of raw data in order to get the absolute TEC values, which are interpolated to get grid values of the map. Even for the same source there are significant differences in the density of monitoring stations according to the region. A case of study concerning scintillation is also analyzed using the corresponding TEC and scintillation maps. TEC maps employed here encompass the years from 2022 to 2024, in the growing phase of the current solar cycle 25. The months of March, June, September and December were selected to take into account the TEC seasonal variation.