Ionospheric Scintillation Events Research Articles

Prediction of Ionospheric Scintillations Using Machine Learning Techniques during Solar Cycle 24 across the Equatorial Anomaly

Ionospheric scintillation is a pressing issue in space weather studies due to its diverse effects on positioning, navigation, and timing (PNT) systems. Developing an accurate and timely prediction model for this event is crucial. In this work, we developed two machine learning models for the prediction of ionospheric scintillation events at the equatorial anomaly during the maximum and minimum phases of solar cycle 24. The models developed in this study are the Random Forest (RF) algorithm and the eXtreme Gradient Boosting (XGBoost) algorithm. The models take inputs based on the solar wind parameters obtained from the OMNI Web database from the years 2010–2017 and Pc5 wave power obtained from the Bear Island (BJN) magnetometer station. We retrieved data from the Scintillation Network and Decision Aid (SCINDA) receiver in Egypt from which the S4 index was computed to quantify amplitude scintillations that were utilized as the target in the model development. Out-of-sample model testing was performed to evaluate the prediction accuracy of the models on unseen data after training. The similarity between the observed and predicted scintillation events, quantified by the R2 score, was 0.66 and 0.74 for the RF and XGBoost models, respectively. The corresponding Root Mean Square Errors (RMSEs) associated with the models were 0.01 and 0.01 for the RF and XGBoost models, respectively. The similarity in error shows that the XGBoost model is a good and preferred choice for the prediction of ionospheric scintillation events at the equatorial anomaly. With these results, we recommend the use of ensemble learning techniques for the study of the ionospheric scintillation phenomenon.

Cooperative Localization under Ionospheric Scintillation Events

Ionospheric scintillation causes major impairments to Global Navigation Satellite System (GNSS) in low-latitude regions. In severe scenarios, this event can lead to complete loss of lock, thus making GNSS measurements unusable for navigation. In this paper, we derive a cooperative localization algorithm where a set of partially connected aircraft exchange messages with neighboring nodes on the network to improve their own position estimates. We consider the scintillation events as abrupt changes in the measurement variance, which are modeled by a discrete-valued Markov process at the nodes which have access to GNSS measurements. Simulation results show that Markovian modeling and cooperation via factor graph message passing reduce the average 3D root mean square localization error and yield an average vertical position error that meets civil aviation standards for approach and landing.

Investigating the Effects of Ionospheric Scintillation on Multi‐Frequency BDS‐2/BDS‐3 Signals at Low Latitudes

AbstractIonospheric scintillation could seriously disrupt the signal tracking of the global navigation satellite systems (GNSS), further causing positioning accuracy degradation or unavailability. BeiDou navigation satellite system (BDS), a newly developed GNSS by China, has begun to provide global positioning, navigation, and timing service. The objective of the present study is to investigate the effects of ionospheric scintillation on BDS‐2 and BDS‐3 multi‐frequency signals. Ionospheric scintillation monitor receiver data from four monitors in Brazil were collected from October 2021 to May 2022. The results illustrate that S4(B2) and S4(B3) linearly increase with S4(B1) for S4(B1) ≤ 0.6, which is consistent with weak scattering theories, and average experimental ratios of S4(B2)/S4(B1), S4(B3)/S4(B1), and S4(B2)/S4(B3) are less than corresponding theoretical ones by 6.1%, 4.4%, and 1.9%, respectively. Meanwhile, as S4 values increase, lower‐frequency scintillation saturates earlier than higher ones, and the probability of ionospheric scintillation events on B2 and B3 signals is approximately twice (S4 ≥ 0.7) as B1 signals in the equatorial ionization anomaly (EIA) regions. To alleviate the undesirable effects of missing data on GNSS positioning, we first investigate the inter‐frequency relationship and distribution probability of two significant spectral parameters, that is, T (the spectral strength of the phase noise at 1 Hz) and p (the spectral slope of the phase power spectral density) in the tracking jitter model among three BDS frequencies. Results show that the performances among B1, B2, and B3 frequencies have a higher correlation respectively, and their values for B2 and B3 signals are more susceptible to be impacted by ionospheric scintillation.

The Movement of GPS Positioning Discrepancy Clouds at a Mid-Latitude Region in March 2015

The geomagnetic storm on 17 March 2015 had a strong impact on the global navigation satellite systems (GNSS) positioning results in many GNSS Continuously Operating Reference Stations (CORS) in Europe. The analysis of global positioning system (GPS) observations in Latvian CORS stations discovered a strong impact of this space weather event over the whole country. The impact appeared as a moving cloud of positioning discrepancies across the country. However, the analysis of the days before 17 March revealed other smaller duration ionospheric scintillation events. The objective was to analyze the GPS positioning discrepancy cloud movement, total electron content (TEC), and rate of change of the TEC index (ROTI) relationships, as well as discrepancy statistics. The area of analysis on 16–18 March was increased by including the EGNOS ground-based Ranging and Integrity Monitoring Stations (RIMS): GVLA and GVLB, LAPA and LAPB, and WRSA and WRSB. The conclusion of the study is that each “shot” after 90 s gives a completely new cloud with a new impacted station subset, its configuration, and completely irregular discrepancy values.

Precursors Identification for Forecasting UHF‐Band Ionospheric Scintillation Events Over Chinese Low‐Latitude Region by Deep Learning

AbstractThe occurrences of the UHF‐band ionospheric scintillation events caused by Equatorial Plasma Bubbles (EPBs) in the low‐latitude region depend on many factors. Nowadays, it is also a hard work for researchers to analyze and find out the useful precursory signatures of the generation of EPBs from several kinds of observations, which is a necessary work to build a forecasting model base on the priori knowledge. Many studies have revealed that there are distinctive features of daytime background ionosphere characteristics on scintillation and nonscintillation days. Deep learning technique (DLT) could automatically discover the distinctive variations from the daytime background ionospheric observations of scintillation and nonscintillation days. It is found that the forecasting problem of postsunset ionospheric scintillation events could be converted to a classification problem, and easily solved by DLT. The effectiveness of DLT for building a forecasting model of the UHF‐band ionospheric scintillation events over Chinese low‐latitude region is studied and evaluated. By analyzing the performance metrics of different combinations of related factors as the input parameters of DLT, a new important precursor for forecasting the UHF‐band ionospheric scintillation events over Chinese low‐latitude region is identified for the first time. It is suggested that the latitudinal and diurnal variations of the transequatorial Total Electron Content (TEC) profile in the east of the forecasting area is one of the key precursors.

Assessing the Positioning Performance Under the Effects of Strong Ionospheric Anomalies With Multi‐GNSS in Hong Kong

AbstractGlobal navigation satellite system (GNSS) precise positioning performance will be strongly affected under severe ionospheric anomaly conditions. The combination of multi‐GNSS can increase the available observations and improve the geometry of continuously tracked satellites. This paper focuses on assessing the positioning performance with the combination of Global Positioning System (GPS), Global'naya Navigatsionnaya Sputnikova Sistema (GLONASS), and BeiDou System (BDS) around the St. Patrick's Day geomagnetic storm (9–18 March) in 2015 in Hong Kong. The rate of total electron content (TEC) index (ROTI) indicates severe ionospheric anomalies before the superstorm, while it was absent during the main phase of the storm in Hong Kong. Furthermore, strong scintillation events on signal‐to‐noise ratio (SNR) and multipath (MP) observables are observed during ionospheric anomalies period. Then the performance of single‐point positioning (SPP) and precise point positioning (PPP) with multi‐GNSS is shown. The ionospheric scintillation events may reduce pseudorange accuracy but affect SPP performance a little in this study, while the PPP accuracy is vastly decreased due to the subsequent reconvergence caused by frequent cycle slip (CS). Compared to PPP solutions with GPS only, the accuracy is improved significantly with the combination of multi‐GNSS.

Semi-Supervised GNSS Scintillations Detection Based on DeepInfomax

This work focuses on a machine learning based detection of ionospheric scintillation events affecting Global Navigation Satellite System (GNSS) signals. We here extend the recent detection results based on Decision Trees, designing a semi-supervised detection system based on the DeepInfomax approach recently proposed. The paper shows that it is possible to achieve good classification accuracy while reducing the amount of time that human experts must spend manually labelling the datasets for the training of supervised algorithms. The proposed method is scalable and reduces the required percentage of annotated samples to achieve a given performance, making it a viable candidate for a realistic deployment of scintillation detection in software defined GNSS receivers.

Comparison of Ground‐Based Ionospheric Scintillation Observations With In Situ Electron Density Variations as Measured by the Swarm Satellites

AbstractIonospheric scintillation is known to be associated with irregularities in electron density, which manifests as rapid fluctuations in the amplitude and phase of radio signals traversing the ionosphere. The scintillations caused by irregularity structures in the ionosphere can be directly measured using ground‐based GPS scintillation measurement receivers. In this work we have used in situ measurements of electron density by means of the Langmuir probe on the Swarm satellites to derive an index called the rate of density index (RODI). Using a ground‐based International Global Navigation Satellite Systems Service receivers and one dedicated scintillation measurement receiver, we have examined if we can identify ionospheric scintillation events that are correlated with space‐based electron density variations characterized by the RODI for cases when the Swarm satellites orbital tracks traverse coincidental locations to the ground‐based station. The selected Swarm B passes over Africa have been limited to the longitudes within ±7° of longitude relative to the position of a dedicated scintillation receiver located at Pwani, Kenya (Geo. Lon: 39.78°E, Geo. Lat: 3.24°S). Our results show that RODI could be a useful index for detecting irregularities associated with scintillation events that can also be observed from the ground. There is a similarity in RODI fluctuations and ground‐based irregularity measures based on rate of total electron content index with an asymmetry in irregularity activity across African region. There is stronger irregularity activity and high background nighttimes electron density on the western side of Africa than on the eastern side. This work shows the potential of using space‐based in situ measurement for scintillation detection and mitigation for operational purposes particularly for regions where terrestrial scintillation measurement are not possible like over oceans and deserts.

The Second-Order Derivative of GPS Carrier Phase as a Promising Means for Ionospheric Scintillation Research

The carrier phase observable is the most preferable means for observation of ionospheric scintillation events. As the ionospheric scintillations show different features at different GNSS frequencies the single-frequency data should be used for complex analysis and data interpretation. The second-order derivative of the GPS signal carrier phase is suggested as a promising means to detect small-scale ionospheric disturbances. The high-rate L1 phase data with no additional processing are used for this purpose. Modeling and experimental results proved the hypothesis. It was revealed the strict dependence of sensitivity of the second-order derivative parameter on GPS receiver hardware features and carrier phase sampling rate.

Detection of GNSS Ionospheric Scintillations Based on Machine Learning Decision Tree

This paper proposes a methodology for automatic, accurate, and early detection of amplitude ionospheric scintillation events, based on machine learning algorithms, applied on big sets of 50 Hz postcorrelation data provided by a global navigation satellite system receiver. Experimental results on real data show that this approach can considerably improve traditional methods, reaching a detection accuracy of 98%, very close to human-driven manual classification. Moreover, the detection responsiveness is enhanced, enabling early scintillation alerts.

Ionospheric scintillation suppression based on chemical release

There occur frequently the ionospheric scintillation events at low and middle latitudes, which seriously affect the radio transmission process of satellite link, resulting in the decline of satellite communication and navigation signal quality and even interrupt. During the gestation period before the ionospheric scintillation, the growth rate of plasma instability can be reduced and thus suppress the scintillation events by releasing the electron density-enhancing chemicals in the ionosphere plasma bubble, filling with plasma bubble, changing the plasma environmental characteristics, and regulating the ionospheric dynamics process. The theory and method of suppressing the ionospheric scintillation based on chemical release are tnvestigated. According to the change of the plasma environment caused by the chemical release, and the quantitatively calculating of the contribution of control factors to the growth rate of instability, an ionospheric scintillation suppression model is built, which is based on chemical release into ionosphere. The process of plasma bubble filling out is simulated and the results of the simulation show that the plasma cloud is completely filled with plasma bubbles after 1200 seconds, which reduces the plasma density gradient and suppresses the growth of plasma instability. The growth of plasma instability decreases from 0.2 before releasing to about 0.0004 after releasing, and no new instability is excited within 20 minutes after the plasma bubble has been filled up. Guangdong, South China Sea and other regions in China are at the peak of equatorial anomalies, and the occurrence rate and severity of scintillation are more significant than those in the equatorial and Polar Regions, thus these regions become the regions where there occur most frequently the scintillation and the most serious influence globally. The research work of this paper will lay a solid theoretical foundation for the technology of suppressing the satellite signal ionospheric scintillation in middle and low latitude area of China.

A study of multi-GNSS ionospheric scintillation and cycle-slip over Hong Kong region for moderate solar flux conditions

This study presents the characteristics of Multiple Global Navigation Satellite System (Multi-GNSS) ionospheric scintillation and cycle-slip occurrence through the analysis of Multi-GNSS data collected by a newly installed receiver located at Sha Tin of Hong Kong from 6 October 2015 to 31 December 2016. This period of time was under a moderate solar activity condition with average sunspot number and F10.7 as 44 and 92, respectively. Considering the frequent occurrence of loss of lock in satellites measurements in the presence of ionospheric scintillation, a rate of geometry-free (ROGF) combination is proposed to take the time gap size between two data arcs into account in the cycle-slip detection. The results show that most ionospheric scintillation events and cycle-slips are observed from 20:00 LT to 0:00 LT. Under the strong scintillation (S4>0.6) conditions, it is found that the time series of wide-land (WL) ambiguity NWL and ROGF vary significantly and their range can reach more than 50 cycles and 0.1m/s, respectively. However, the variations of the NWL and ROGF are generally small under weak scintillation (0.2<S4≤0.6) or non-scintillation (S4≤0.2) conditions. A strong correlation of scintillation and cycle-slip occurrence is also verified by the daily and spatial statistics results. In addition, it is found that on average every 1000 strong scintillation events can result in 200, 124, and 171 cycle-slip occurrences in GPS, GLONASS, and BDS, respectively, whereas these values are 7, 12, and 12 per 1000 under weak scintillation conditions. This study suggests that cautions be taken when GNSS measurements are contaminated by the strong ionospheric scintillation in GNSS applications such as real-time kinematic (RTK) and precise point positioning (PPP).

Characterization of high‐latitude ionospheric scintillation of GPS signals

AbstractThis paper presents statistical analysis of arctic auroral oval ionospheric scintillation events during the current solar maximum based on high‐rate Global Positioning System data collected in Gakona, Alaska (62.39°N, 145.15°W) from August 2010 to March 2013. The objective is to gain a better understanding of the climatology and morphology of ionospheric scintillation in high‐latitude regions. A scintillation event filter, multipath identification procedures, and other processes are applied to exclude nonscintillation related signal intensity and phase fluctuation and to extract scintillation events with S4 index above 0.12 and phase sigma above 6° from over 657 days of data. A total of over 5800 scintillation events were identified; most of them show phase fluctuations, only 10% of the phase fluctuations are accompanied by weak amplitude scintillation. Based on the occurrence time, signal direction of arrival, intensity, and duration of these scintillation events and the solar and geomagnetic activities associated with these events, diurnal, seasonal, spatial, and solar activity dependencies are derived and presented in the paper.

On the distribution of GPS signal amplitudes during low-latitude ionospheric scintillation

Ionospheric scintillations are fluctuations in the phase and/or amplitude of trans-ionospheric radio signals caused by electron density irregularities in the ionosphere that affect the performance of Global Navigation Satellite Systems receivers. We used an entire month of high-rate (50 Hz) measurements of the GPS L1 (1.575 GHz) signal amplitude to investigate the statistics of L-Band signals during ionospheric scintillation events. The scintillation measurements used in this study were made by a GPS-based scintillation monitor installed in Sao Jose dos Campos, Brazil, near the equatorial anomaly peak. The observations were made over 32 days during high solar flux conditions when typical values of F10.7 were above 150 A— 10Â?22 W/m2/Hz. This data set allowed us to test the Nakagami-m and Rice probability density functions (PDFs) in the description of the distribution of L-Band scintillating signals with better statistical confidence than previously possible. In addition, we parameterized and tested the ability of the Â?---μ distribution, which is a more general and yet simple and flexible fading model to describe the distribution of signal amplitudes during scintillation events. The results show a slight advantage of the Nakagami-m PDF over the Rice distribution. We also show that the Â?---μ PDF outperforms the Nakagami-m and Rice PDFs in the statistical characterization of amplitude scintillation. The reason for such a performance is the fact that the Â?---μ model was specially tailored to the ionospheric scintillation events, resulting in a better fit with experimental data, specifically in the region of small amplitudes, which is particularly interesting for scintillation studies.

Analysis of strong ionospheric scintillation events measured by means of GPS signals at low latitudes during disturbed conditions

Drifting structures characterized by inhomogeneities in the spatial electron density distribution at ionospheric heights cause the scintillation of radio waves propagating through. The fractional electron density fluctuations and the corresponding scintillation levels may reach extreme values at low latitudes during high solar activity. Different levels of scintillation were observed on experimental data collected in the Asian sector at low latitudes by means of a GPS dual frequency receiver under moderate solar activity (2005). The GPS receiver used in these campaigns was particularly modified in firmware in order to record power estimates on the C/A code as well as on the carriers L1 and L2. Strong scintillation activity was recorded in the post‐sunset period (saturatingS4 and SI as high as 20 dB). Spectral modifications and broadening was observed during high levels of scintillation possibly indicating refractive scattering taking place instead of diffractive scattering. A possible interpretation of those events was attempted on the basis of the refractive scattering theory developed by Uscinski (1968) and Booker and MajidiAhi (1981).

Analysis of the PLL phase error in presence of simulated ionospheric scintillation events

The functioning of standard phase locked loops (PLL), including those used to track radio signals from Global Navigation Satellite Systems (GNSS), is based on a linear approximation which holds in presence of small phase errors. Such an approximation represents a reasonable assumption in most of the propagation channels. However, in presence of a fading channel the phase error may become large, making the linear approximation no longer valid. The PLL is then expected to operate in a non‐linear regime. As PLLs are generally designed and expected to operate in their linear regime, whenever the non‐linear regime comes into play, they will experience a serious limitation in their capability to track the corresponding signals. The phase error and the performance of a typical PLL embedded into a commercial multiconstellation GNSS receiver were analyzed in presence of simulated ionospheric scintillation. Large phase errors occurred during scintillation‐induced signal fluctuations although cycle slips only occurred during the signal re‐acquisition after a loss of lock. Losses of lock occurred whenever the signal faded below the minimumC/N0threshold allowed for tracking. The simulations were performed for different signals (GPS L1C/A, GPS L2C, GPS L5 and Galileo L1). L5 and L2C proved to be weaker than L1. It appeared evident that the conditions driving the PLL phase error in the specific case of GPS receivers in presence of scintillation‐induced signal perturbations need to be evaluated in terms of the combination of the minimumC/N0 tracking threshold, lock detector thresholds, possible cycle slips in the tracking PLL and accuracy of the observables (i.e. the error propagation onto the observables stage).