Short-term estimation of GNSS TEC using a neural network model in Brazil

Ionospheric TEC modelling for earthquakes precursors from GNSS data

Implementing the International GNSS Service 2021+ Strategic Plan: Vision and Use Cases

Mapping of the Ionospheric Total Electron Content over the East African Low–Latitude Region

Abstract. Turkey is a country located in the middle latitude zone, where tectonic activity is intensive. Recently, an earthquake of magnitude 6.5 Mw occurred offshore in the Aegean Sea on 24 May 2014 at 09:25 UTC, which lasted about 40 s. The earthquake was also felt in Greece, Romania, and Bulgaria in addition to Turkey. In recent years, ionospheric anomaly detection studies have been carried out because of seismicity with total electron content (TEC) computed from the global navigation satellite system's (GNSS) signal delays and several interesting findings have been published. In this study, both TEC and positional variations have been examined separately following a moderate size earthquake in the Aegean Sea. The correlation of the aforementioned ionospheric variation with the positional variation has also been investigated. For this purpose, a total of 15 stations was used, including four continuously operating reference stations in Turkey (CORS-TR) and stations in the seismic zone (AYVL, CANA, IPSA, and YENC), as well as international GNSS service (IGS) and European reference frame permanent network (EPN) stations. The ionospheric and positional variations of the AYVL, CANA, IPSA, and YENC stations were examined using Bernese v5.0 software. When the precise point positioning TEC (PPP-TEC) values were examined, it was observed that the TEC values were approximately 4 TECU (total electron content unit) above the upper-limit TEC value at four stations located in Turkey, 3 days before the earthquake at 08:00 and 10:00 UTC. At the same stations, on the day before the earthquake at 06:00, 08:00, and 10:00 UTC, the TEC values were approximately 5 TECU below the lower-limit TEC value. The global ionosphere model TEC (GIM-TEC) values published by the Centre for Orbit Determination in Europe (CODE) were also examined. Three days before the earthquake, at all stations, it was observed that the TEC values in the time period between 08:00 and 10:00 UTC were approximately 2 TECU above the upper-limit TEC value; 1 day before the earthquake at 06:00, 08:00, and 10:00 UTC, the TEC values were approximately 4 TECU below the lower-limit TEC value. Again, by using the same 15 stations, positional variation investigation for before and after the earthquake was undertaken for the AYVL, CANA, IPSA, and YENC stations. As a result of the conducted analysis, positional displacements were seen before and after the earthquake at the CANA station, which is the nearest station to the earthquake centre. Before and after the earthquake, positional displacements were observed as 10 and 3 cm respectively.

Modeling of GPS-TEC using QR-decomposition over the low latitude sector during disturbed geomagnetic conditions

Abstract. The impact of space weather events on satellite-based technologies (e.g. satellite navigation and precise positioning) is typically quantified on the basis of the total electron content (TEC) and temporal fluctuations associated with it. GNSS (global navigation satellite systems) TEC measurements are integrated over a long distance and thus may include contributions from different regions of the ionised atmosphere which may prevent the resolution of the mechanisms ultimately responsible for given observations. The purpose of the experiment presented here was to compare TEC estimates from EISCAT and GPS measurements. The EISCAT measurements were obtained along the same line of sight of a given GPS satellite observed from Tromsø. The present analyses focussed on the comparison of temporal fluctuations in the TEC between aligned GPS and EISCAT measurements. A reasonably good agreement was found between temporal fluctuations in TEC observed by EISCAT and those observed by a co-located GPS ionospheric monitor along the same line of sight, indicating a contribution from structures at E and F altitudes mainly to the total TEC in the presence of ionisation enhancements possibly caused by particle precipitation in the nighttime sector. The experiment suggests the great potential in the measurements to be performed by the future EISCAT_3D system, limited only in the localised geographic region to be covered.

On the possible contribution of ionospheric vertical drifts to TEC modelling in low latitudes

With the capability to record Global Navigation Satellite Systems (GNSS) data at high-rate, at sampling rates typical for seismological applications, experiments are needed to quantify the response of GNSS to shaking from earthquakes. There have been a few studies that examine the response of GNSS to strong shaking. Recently, Ebinuma and Kato (2012) used a global positioning system (GPS) simulator to electronically test several GNSS receivers and obtain the receiver characteristics at three frequencies: 1, 2, and 5 Hz. The results showed that the amplitude of 5-Hz displacements recorded by the GPS was, depending on the receiver model, between 30 and 125 percent more than the displacement input to the simulator. At low frequencies, the GPS displacement was nearly equal to the input displacement. In addition, Ebinuma and Kato (2012) examined how each receiver model amplified an earthquake displacement record in the 2–8 Hz band. The study discussed here builds on the tests by Ebinuma and Kato (2012), but rather than using electronic simulation, the tests are setup outdoors and closer to actual field installations of GNSS equipment. The authors used a one-dimensional shake table capable of 400 mm of displacement and high acceleration; the shake table also is constrained by a precision linear slider to have very low tilt that would affect inertial sensors. In addition, the stage position can be accurately monitored independent of the GNSS hardware and, importantly, provides a reference to compare with the estimated displacements from the GNSS data. The tests spanned a greater frequency range from 0.2 to 20 Hz and used equipment from three different manufacturers covering five different combinations of receivers and antennas. In addition, the authors have been able to simulate the frequency response of the GNSS equipment using a simple, causal filter. The quality of the filter was tested using additional test data where a step function in displacement was applied to the shake table. The observed displacements from the GNSS data show an overshoot in displacement at the time of the step or transition of the stage. That overshoot was accurately predicted using the filter design derived from the sinusoidal displacement tests.

A Global Navigation Satellite System (GNSS) receiver is, to some extent, a “black box” when its data is used for ionospheric studies. Our results based on Javad, Septentrio, Trimble, and Leica GNSS receivers have proven that the accuracy of the slant Total Electron Content (TEC) calculation can differ significantly depending on the GNSS receiver type/model, because TEC measurements depend on the carrier phase tracking technique applied in a receiver. The correlation coefficient between carrier phase noise in L1 and L2 channels is considered as a possible indicator that shows if the L1-aided tracking technique or independent tracking is applied inside a receiver. An empirical model of the TEC noise component was provided to determine the TEC noise value in different types/models of GNSS receivers.

Ionospheric total electron content (TEC) is one of the key parameters for users of radio-based systems, such as the Global Navigation Satellite System, high-frequency communication systems, and space-based remote sensing systems, since total ionospheric delay is proportional to TEC through the propagation path. It is important to know extreme TEC values in readiness for hazardous ionospheric conditions. The purpose of this study is to estimate extreme TEC values with occurrences of once per year, 10 years, and hundred years in Japan. In order to estimate the extreme values of TEC, a cumulative distribution function of daily TEC is derived using 22 years of TEC data from 1997 to 2018. The extreme values corresponding to once per year and 10 years are 90 and 110 TECU, respectively, in Tokyo, Japan. On the other hand, the 22-year data set is not sufficient to estimate the once-per-100-year value. Thus, we use the 62-year data set of manually scaled ionosonde data for the critical frequency of the F-layer (foF2) at Kokubunji in Tokyo. First, we study the relationship between TEC and foF2 for 22 years and investigate the slab thickness. Then the result is applied to the statistical distribution of foF2 data for 62 years. In this study, two methods are applied to estimate the extreme TEC value. In the first method, the distribution of slab thickness is artificially inflated to estimate extreme TEC values. In the second method, extreme slab thicknesses are applied to estimate extreme TEC values. The result shows that the once-per-100-year TEC is about 150–190 TECU at Tokyo. The value is also estimated to be 180–230 TECU in Kagoshima and 120–150 TECU in Hokkaido, in the southern and northern parts of Japan, respectively.

<p>The development of space-geodetic observation techniques has brought out a wide range of applications such as positioning and navigation, where the Global Navigation Satellite System (GNSS) is the main tools to provide surveying measurements in these applications. Though GNSS signals enable the calculation of receiver's position, some errors restrict their accuracy. Among these errors, the ionospheric delay is considered as an important error source in the Standard Point Positioning (SPP) applications. Empirical ionospheric models such as Klobuchar, International Reference Ionosphere (IRI), and NeQuick are often applied for computing the Total Electron Content (TEC) within ionosphere and its equivalent delays. However the simulation and forecasting skills of these models are limited due to the simplified model structures and model sensitivity to the calibration period. In this study, we present a novel sequential Calibration approach based on the Ensemble Kalman Filter (C-EnKF) to improve the performance of TEC estimations for SPP applications. To demonstrate the results, the IRI model is used as our basis and the TEC estimates from 56 IGS stations in Europe are applied as observation. The C-EnKF is applied to calibrate some selected model parameter so that IRI can be tuned over Europe. The numerical assessments are performed against the TEC estimates from dual frequency GNSS measurements and against the final IONEX products (that are available with 11 days delays). Based on the forecasting results (during September 2017), we show that the accuracy of TEC estimates from the C-EnKF is improved in the range of 3.7-64.87% compared to IRI. <strong>Keywords: </strong>Ionosphere, Sequential Calibration, Ensemble Kalman Filter (EnKF), IRI, Total Electron Content (TEC), Standard Point Positioning (SPP), GNSS</p>

The ionospheric delay of global navigation satellite systems (GNSS) signals typically is compensated by adding a single correction value to the pseudorange measurement of a GNSS receiver. Yet, this neglects the dispersive nature of the ionosphere. In this context we analyze the ionospheric signal distortion beyond a constant delay. These effects become increasingly significant with the signal bandwidth and hence more important for new broadband navigation signals. Using measurements of the Galileo E5 signal, captured with a high gain antenna, we verify that the expected influence can indeed be observed and compensated. A new method to estimate the total electron content (TEC) from a single frequency high gain antenna measurement of a broadband GNSS signal is proposed and described in detail. The received signal is de facto unaffected by multi-path and interference because of the narrow aperture angle of the used antenna which should reduce the error source of the result in general. We would like to point out that such measurements are independent of code correlation, like in standard receiver applications. It is therefore also usable without knowledge of the signal coding. Results of the TEC estimation process are shown and discussed comparing to common TEC products like TEC maps and dual frequency receiver estimates.

Space weather, geomagnetic, and ionospheric conditions have been identified as the single most influential cause of the Global Navigation Satellite System (GNSS) positioning performance degradation and disruption. The random nature of the appearance, development and intensity of GNSS ionospheric events renders them particularly hard to describe with a single global model. Moderate to massive space weather disturbances remains unresolved problem for satellite navigation. Here the problem of modelling Total Electron Content (TEC), an outcome of ionospheric conditions that affects GNSS positioning performance, in moderately disturbed geomagnetic field conditions, is addressed based on the experimental observations of geomagnetic field and their statistical properties. Here the problem of modelling Total Electron Content in moderately disturbed geomagnetic field conditions, as the originator of the ionospheric conditions, is addressed based on the experimental observations of geomagnetic field and their statistical properties. Three statistical learning-based models are developed, and their performance is assessed according to their ability to predict the resulting TEC. Statistical learning-based TEC prediction models are assessed for their performance, and recommendations for their utilizations are given. The research will continue with development of a larger database of observations taken at various observation sites and during differently generated moderate geomagnetic events. This database will allow for development of more robust TEC prediction models using statistical learning methods for self-adaptive mitigation of GNSS ionospheric effects for the core GNSS positioning performance improvement utilized with a wide rage of GNSS applications.

Global Navigation Satellite System (GNSS) is a navigation system that uses satellite signals to determine its position, which consists of several satellites arranged in a constellation system. GNSS transmits signals to receivers on Earth. The GNSS receiver determines the user’s position, speed, and time by processing the signals transmitted by the satellites. The initial purpose of launching the GNSS was for navigation purposes, but along with its development, GNSS can be used for the purposes of observing deformation of the earth’s crust and in studying the atmosphere. The delayed wave data when passing through the ionosphere can be used to obtain Total Electron Content (TEC) values which then used to study ionospheric disturbances. Ionospheric disturbances are caused by various phenomena, the most common one is the ionospheric disturbances caused by the induction of acoustic and gravitational waves excited by co seismic crustal motions from large earthquakes. Ionospheric disturbances that happened before an earthquake are called Pre-seismic Ionospheric Disturbances and those that occur after an earthquake are called Co-seismic Ionospheric Disturbances (CID). Most studies of ionospheric disturbances still provide information on the timing and value of TEC anomalies in 2D form. Therefore, in this study, a 3D ionosphere profile modelling using computed 3D tomography will be carried out. The 3D information provided is in the form of time, ionosphere altitude and TEC anomaly value by utilizing GNSS data. The TEC anomaly value is obtained from the calculation of linear combination of the ionosphere. This study aims to obtain a spatial and temporal analysis of the CID caused by the West Sumatra Earthquake on March 2, 2016.

The generation of traveling ionospheric disturbances (TIDs) near solar terminators has been predicted, and several studies have reported the detection of TIDs associated with sunrise. However, there are also observations that do not show TID signatures at sunrise. We address this issue by investigating false TID detection at sunrise using total electron content (TEC) data from the global navigation satellite system (GNSS) network over the United States and plasma density measurements from the first Republic of China satellite (ROCSAT‐1). The TEC morphology near sunrise, characterized by a rapid TEC increase, creates significant deviations between observed and trend (or filtered) TEC values. The collective pattern of this difference (dTEC) appears as a negative dTEC band aligned with sunrise. While this feature can be interpreted as a signature of large‐scale TIDs (LSTIDs), it may also falsely suggest a high occurrence rate of medium‐scale TIDs (MSTIDs) when dTEC is used as a detection proxy. However, the negative dTEC band at sunrise is not indicative of LSTIDs because the rapid TEC transition at sunrise is caused by photoionization. This interpretation is supported by the detection of a similar dTEC band at sunrise in model outputs that contain no TID information. Furthermore, the distribution of electron density irregularities derived from ROCSAT‐1 showed no evidence of enhanced MSTID activity near sunrise. Therefore, false TID detections near sunrise in GNSS TEC data should not be overlooked.