Classification of Sources of Ionospheric Scintillation in High Latitudes through Machine Learning

The performance of Global Navigation Satellite Systems (GNSS) can be highly impacted by the interaction of the radio communication signal with ionized particles in the upper layers of the atmosphere (ionosphere). Depending on the shape of the cloud of particles, which is the irregularity, and its speed, the signal can be distorted gravely by intense oscillating signatures called scintillations. Those irregularities and their structures are only understood in-depth for particular events and case studies. In this study, we want to make use of the years of data available for high-rate high magnetic latitude GPS data. To gain a deeper insight into scintillations from multiple sources, we are investigating different machine learning approaches to classify and categorize scintillation events and draw conclusions about physical background processes. For the geomagnetic storm on the 9th of March 2012, we applied a hierarchical clustering analysis on high rate data in phase and power to categorize the temporal scintillation signatures according to their geomagnetic source region. We can distinguish manually selected events from stations inside the polar cap vs those from the auroral oval. From the geomagnetic background data, we are finding input features that will add the most efficiency to our model to detect the scintillation signatures caused by different irregularities and extract those candidate events. Based on this evolving database of events we expect to estimate the importance of the major sources of scintillation in each of the source regions and have a starting point for future studies with CNN and wavelet analysis

Implementation of Machine Learning Methods for Ionospheric Scintillation Data Analysis

The ionosphere is a region in the Earth’s upper atmosphere, where atoms are ionized due to solar radiation. The behavior of the ionosphere depends on time and location, and it is highly influenced by solar activity. The ionization process creates layers of free electrons at different altitudes, which can cause fluctuations in electromagnetic waves crossing the region. The effect of ionospheric events on radio signals can be measured using Global Navigation Satellite Systems (GNSS) receivers, in terms of ionospheric scintillation and Total Electron Content (TEC). The GNSS team at the Space Physics Research Lab (SPRL) studies ionospheric events using multi-frequency GNSS receivers (NovAtel GPStation-6) capable measuring high and low rate scintillation data as well as TEC values from three different GNSS systems (GPS, GALILEO, and GLONASS). The purpose of this project is to develop a machine learning algorithm, using recurrent neural networks, to detect ionospheric events in low-rate scintillation data. Recurrent neural networks are often used for time-series applications, including forecasting and prediction. The model is being trained using data collected by the GNSS receivers in multiple locations (including Daytona Beach), with a focus on high-latitude data from the Canadian High Artic Ionospheric Network (CHAIN). The machine learning model will be integrated with the Embry-Riddle Ionospheric Scintillation Algorithm (EISA), an existing model capable of processing ionospheric data. EISA was developed by the GNSS team at SPRL. The updated model will allow the team to automate the process of ionospheric event detection, which is currently done manually. Upon this implementation, EISA will become an end-to-end model for ionospheric data collection, processing, and modelling

GNSS Observations of Ionospheric Disturbances Due to Rocket Launches

This rising project focuses on the impact rocket launches have on the GNSS satellite constellation in the form of ionospheric scintillation. Disturbance in the ionosphere comes from changing electron densities and a culmination of waves. A large-scale rocket launch is a unique phenomenon that can induce such an event due to its magnitude of power. Structures that form in the ionosphere can manipulate the ability of a GPS receiver to maintain signal contact, risking position data and threatening the economies that depend on it. In order to further understand this issue, Embry-Riddle’s Space Physics Research Lab (SPRL) team has organized a study that focuses on rocket launches that occur in Cape Canaveral, FL. GPS receivers located in the lab collect low and high rate data. This information is then put through a series of MATLAB and python codes developed by SPRL students that parses and creates graphs that take into consideration variables such as TEC (total electron content), phase, and power of signals during launch events. The team has been able to parse and locate scintillation readings. Developments in the near future include looking for patterns in scintillation occurrences, influential environmental factors, and probability assessments

Investigating the Correlation between GNSS Signal Scintillation and Thunderstorms

Global Navigation Satellite Systems (GNSS) have wide application in multiple sectors from daily life to industrial use. These sectors include navigation, timing, and positioning which all require a constant stream of accurate data. One aspect of maintaining the accuracy involves a deep understanding of the ionosphere and how it affects radio signals. This project takes into account an element that might impact the ionosphere: thunderstorms and their high-altitude lightning. Structures created in the ionosphere can cause scintillations, but finding if thunderstorms could initiate these structures is the main goal. Scintillation refers to fluctuations in the phase and amplitude of GNSS signals. There are some forms of lightning, such as blue jets and sprites, that have the ability to reach the ionosphere. This high-altitude lighting is thought to mostly occur in the tropics because of favorable conditions, but it has been observed in other latitudes. Lightning is shown to reach and affect the upper atmosphere, but the effect this could have on satellite signals is still under review. To record relevant scintillations, GNSS receivers have been situated in Daytona Beach, FL and the weather has been monitored for thunderstorms around the area. Receiver data is then graphed and analyzed for significant scintillations during the times of thunderstorms. Lightning location and time is also overlaid on a map with the satellite location plotted to further prove possible correlation between GNSS scintillations and lighting strikes. An evident correlation between scintillation signals and lightning strikes has been observed, but more evidence is needed to confirm this lightning could be the cause of the scintillation

Investigation into GNSS Ionospheric Scintillation from Thunderstorms in Daytona Beach, FL

The Global Navigation Satellite Systems (GNSS) has a wide variety of applications in today’s world, spanning multiple diverse industries. GNSS aids in providing data related to tracking and navigation. This network of vital information requires support, maintenance, and security. Several factors, such as space weather, are thought to have an impact on signals received from GNSS. This project is an ERAU Space Physics Research Lab (SPRL) initiative to better understand the effect that thunderstorms can have on these communications. The project will concentrate on mid-latitude regions within the ionosphere and analyze variables such as total electron content (TEC) in locating fluctuations of radio signals concurrent with thunderstorm periods in Daytona Beach. These fluctuations are also commonly known as ionospheric scintillation. The project builds upon the work of SPRL students from 2018 that utilized ERAU receivers to begin finding unique events of this phenomenon through various algorithms. The 2021 project will look to expand the task by finding and understanding more noteworthy events using recent developments such as the Embry-Riddle Ionospheric Scintillation Algorithm (EISA), with the added challenge of pinpointing lightning data in conjunction with scintillation appearances

Total Electron Content and Ionospheric Scintillation Measurements during the Total Solar Eclipse of July 2, 2019

Global Navigation Satellite Systems (GNSS) provide a reliable source of radio wave signals that is available at all times throughout the entire planet. These signals are known to also interact with the ionosphere, where there is a high concentration of free electrons and ions. This in turn creates a framework for scientists to continuously monitor and analyze how these signals are affected by free electron and ion concentration irregularities in this region. Such irregularities may induce fluctuations in both signal amplitude and phase known as ionospheric scintillations. The behavior of the ionosphere is also known to be directly related with solar activity as well as localized phenomena, such as solar eclipses. This study aims to measure the impact of the solar eclipse of July 2, 2019 on local ionospheric properties in terms of total electron content (TEC) and scintillation indices S4 and SigmaPhi. Two GNSS receivers (NovAtel GPStation-6) were stationed in La Serena, Chile in collaboration with the University of La Serena and in Cerro Pachón, Chile along the Andes Lidar Observatory, where they collected TEC and scintillation data prior, during and after totality. We have observed a pronounced drop and recovery of TEC on both stations as well as supporting high rate data to explore possibilities of eclipse induced scintillations

Investigation into Geomagnetic storms and ionospheric scintillation

Understanding how space weather phenomenon affects daily life has been a main focus of space weather studies. In particular, identifying the relationship between solar activities, ionospheric irregularities and consequently ionospheric scintillation has inspired numerous research efforts. Geomagnetic storms fueled by solar activities cause ionospheric irregularities. Ionospheric scintillation occurs when radio signals travel through these irregularities and experience rapid fluctuations in radio signal phase and amplitude. Such fluctuations have great consequences in radio wave based technology such as the Global Position system(GPS) as it causes a loss of lock. Therefore, through the implantation of two GPS Receivers, continuous data was obtained on phase and amplitude of radio signals from the Global Navigation Satellite Systems(GNSS). This data was then thoroughly analyzed to identify scintillation signatures. On January 31st, 2019, scintillation signatures that correlated to a G1 minor geomagnetic storm were observed. In this paper, the method of analysis is adapted from the aforementioned case study to identify past geomagnetic events that possibly correlated with observed scintillation. Through this study, it is hoped that a correlation between geomagnetic storms and ionospheric scintillation in the mid-latitude region will be highlighted

Categorizing Characteristic Regions of Nightside High-Latitude Ionospheric Irregularities Using a Machine Learning Approach.

We are making use of the vast amount of publicly available GNSS data to develop a data driven supervised machine learning model to categorize to a predefined set of characteristic high-latitude ionospheric irregularity nightside regions. The goal of this model is to predict whether the scintillating instance of high-frequency data was recorded in the auroral oval vs. the polar cap with a high level of confidence. The source regions were determined using the SUSSI instruments onboard the DMSP satellites. The model is trained and tested with events extracted by thresholding the low-rate data from receivers from both characteristic nightside regions. As input parameters of the model serve the Power Spectral Densities (PSD) of the events since they provide context about the size and velocities of the irregularities. The model is expected to identify potential distinct characteristics of each predefined source region and in a second step to predict the region based on a given phase or amplitude time series. This will allow us to further understand of the characteristics of ionospheric irregularities and their sources

An Investigation Into the Relationship Between Lightning and GNSS Signal Disturbances in Daytona Beach, FL

Ionospheric scintillations can affect the Global Navigation Satellite System’s (GNSS) signals by disrupting the radio waves as they travel through the upper atmosphere. Space weather events are known to cause variations in the total electron content (TEC) of the ionosphere in high and low latitude regions, leading to these scintillations. However, the extent to which these scintillations occur in the mid-latitude region and their causes is under-examined. The goal of our research is to better analyze disruptions to ground-based receivers and GNSS signals by determining whether lightning strikes cause ionospheric scintillations and other interferences with GNSS satellites. As the lightning capital of the world, Florida is an ideal place to record a large data set of thunderstorms. Using high rate (50Hz) multi constellation GNSS receivers at Daytona Beach, FL on the Embry-Riddle University campus, we parse and filter the scintillation data to obtain signal phase and amplitude fluctuations that are coincident with thunderstorms. For finding spatial correlation we compare ionospheric pierce points (IPP) of the satellites on which we observed fluctuations with a data set of lightning strikes and their coordinates, type, and peak current. After analysis of approx. 185+ hours of thunderstorm data, we have observed power drops which are most likely interference at the receiver end associated with lightning. We observed drops in the power of GNSS data on almost all visible satellite signals during the thunderstorms and we are further investigating anomalous peaks/ drops in power which are not visible on all available satellites--possibly related to more localized events. If a direct relationship is found between thunderstorms and scintillation, it would provide a better understanding of tropospheric effects on the ionosphere, besides assisting in improving the reliability of GPS receivers