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Local mitigation of higher-order ionospheric effects in DFMC SBAS and system performance evaluation
(2024-04-01)
Sophan, Somkit
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Supnithi, Pornchai
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Myint, Lin M.M.
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Saito, Susumu
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Hozumi, Kornyanat
Dual-frequency multi-constellation (DFMC) satellite-based augmentation system (SBAS) is a new SBAS standard for aeronautical navigation systems. It supports aircraft navigation from the enroute to approach phases via the L1 and L5 frequencies (1575.42 and 1176.45 MHz). Although the ionosphere-free (IF) combination in the DFMC SBAS operation removes the first-order ionospheric delays in the pseudorange measurement, remaining terms including the satellite-clock offset errors and higher-order ionospheric (HOI) delays are still unaccounted for. The DFMC SBAS accuracy and integrity can be affected by the HOI effects, especially during severe ionospheric disturbances. In this work, we present the local DFMC SBAS corrections with and without the mitigation of HOI delays. We first estimate the HOI delay terms using the received pseudorange followed by separate satellite and receiver bias estimations based on the minimum sum-variance technique. The integrity terms can then be obtained. The performances of DFMC SBAS using the global navigation satellite system (GNSS) data including GPS, Galileo, and QZSS are evaluated using obtained GNSS data at stations in Thailand on the ionospheric quiet and disturbed days. The results show that with the HOI mitigation, the vertical positioning errors (VPE) on the quiet and disturbed days can be improved by 12% and 9%, whereas the vertical protection levels (VPL) are improved by 16% and 21%, respectively. In addition, we perform a preliminary assessment of DFMC SBAS based on the International Civil Aviation Organization (ICAO) requirements of two categories: Localizer Performance with Vertical guidance (LPV-200) and Category I precision approach (CAT-I) showing promising results.
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Simultaneous equatorial plasma bubble observation using amplitude scintillations from GNSS and LEO satellites in low-latitude region
(2023-12-01)
Seechai, Khanitin
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Myint, Lin Min Min
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Hozumi, Kornyanat
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Nishioka, Michi
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Saito, Susumu
This study estimates the scale sizes of the plasma density irregularities and the longitudinal width associated with equatorial plasma bubbles (EPBs) in equatorial and low-latitude regions. By analyzing amplitude scintillation S<inf>4</inf> indices and total electron content (TEC) measured from low earth orbit (LEO) satellite’s beacon signals with 400 MHz and Global Navigation Satellite System (GNSS) L1/E1 signals with 1575.42 MHz, recorded by receivers at the KMITL station in Bangkok, Thailand (geographic; 13.73° N, 100.77°E, magnetic: 7.26°N), we investigate the characteristics of these irregularities. We collected data of 154 LEO satellite pass events during nighttime on 21 disturbed days in four equinoctial months in 2021. Based on the presence or absence of the scintillation effects on GNSS and LEO beacon signals, the events are categorized into four classes to estimate the scale size of the plasma density irregularities. The analysis suggests that events with both GNSS and LEO scintillations, as well as events with GNSS scintillation alone, occur predominantly before midnight assuming the presence of the small-scale size of the irregularities within EPB. However, events with only LEO scintillation occur throughout the whole night and some events are observed before the events with both GNSS and LEO scintillations. Post-sunset LEO scintillation alone may be attributed to the onset of EPBs developing at low altitude, while post-midnight LEO scintillation events near the magnetic equator, observed during periods of low GNSS Rate of TEC Index (ROTI) values, are associated with bottom-side ionospheric irregularities but are not linked with EPB. The findings are consistent with previous researches on the generation and decay of electron density irregularities within plasma bubbles. However, this study provides new insights by using specific data sets and analysis techniques, offering a more comprehensive understanding of the association of LEO scintillations with bottom-side ionospheric irregularities near the magnetic equator, not observed in the ROTI map. Graphical Abstract: [Figure not available: see fulltext.]
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Equatorial spread-F forecasting model with local factors using the long short-term memory network
(2023-12-01)
Thammavongsy, Phimmasone
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Supnithi, Pornchai
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Myint, Lin Min Min
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Hozumi, Kornyanat
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Lakanchanh, Donekeo
The predictability of the nighttime equatorial spread-F (ESF) occurrences is essential to the ionospheric disturbance warning system. In this work, we propose ESF forecasting models using two deep learning techniques: artificial neural network (ANN) and long short-term memory (LSTM). The ANN and LSTM models are trained with the ionogram data from equinoctial months in 2008 to 2018 at Chumphon station (CPN), Thailand near the magnetic equator, where the ESF onset typically occurs, and they are tested with the ionogram data from 2019. These models are trained especially with new local input parameters such as vertical drift velocity of the F-layer height (Vd) and atmospheric gravity waves (AGW) collected at CPN station together with global parameters of solar and geomagnetic activity. We analyze the ESF forecasting models in terms of monthly probability, daily probability and occurrence, and diurnal predictions. The proposed LSTM model can achieve the 85.4% accuracy when the local parameters: Vd and AGW are utilized. The LSTM model outperforms the ANN, particularly in February, March, April, and October. The results show that the AGW parameter plays a significant role in improvements of the LSTM model during post-midnight. When compared to the IRI-2016 model, the proposed LSTM model can provide lower discrepancies from observational data. Graphical Abstract: [Figure not available: see fulltext.].
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Classification of the equatorial plasma bubbles using convolutional neural network and support vector machine techniques
(2023-12-01)
Thanakulketsarat, Thananphat
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Supnithi, Pornchai
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Myint, Lin Min Min
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Hozumi, Kornyanat
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Nishioka, Michi
Equatorial plasma bubble (EPB) is a phenomenon characterized by depletions in ionospheric plasma density being formed during post-sunset hours. The ionospheric irregularities can lead to disruptions in trans-ionospheric radio systems, navigation systems and satellite communications. Real-time detection and classification of EPBs are crucial for the space weather community. Since 2020, the Prachomklao radar station, a very high frequency (VHF) radar station, has been installed at Chumphon station (Geographic: 10.72° N, 99.73° E and Geomagnetic: 1.33° N) and started to produce radar images ever since. In this work, we propose two real-time plasma bubble detection systems based on support vector machine techniques. Two designs are made with the convolutional neural network (CNN) and singular value decomposition (SVD) used for feature extraction, the connected to the support vector machine (SVM) for EPB classification. The proposed models are trained using quick look (QL) plot images from the VHF radar system at the Chumphon station, Thailand, in 2017. The experimental results show that the combined CNN-SVM model, using the RBF kernel, achieves the highest accuracy of 93.08% while the model using the polynomial kernel achieved an accuracy of 92.14%. On the other hand, the combined SVD-SVM models yield the accuracies of 88.37% and 85.00% for RBF and polynomial kernels of SVM, respectively. Graphical Abstract: [Figure not available: see fulltext.].
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Instrumental Receiver Bias Estimation for Ionospheric Total Electron Content by Neural Network Model
(2023-10-01)
Thu, Phyo C.
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Supnithi, Pornchai
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Budtho, Jirapoom
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Saekow, Apitep
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Sopon, Thanomsak
Total Electron Content (TEC) is one of the most important parameters in the study of the ionosphere, especially for determining ionospheric disturbances. The TEC levels are typically estimated from dual-frequency GPS observation data. Since the measured TEC contains discrepancies such as satellite and receiver biases, they need to be removed to obtain more accurate TEC values. In this work, we estimate the receiver bias using a neural network technique. Based on the exhaustive evaluation, we design a neural network (NN) model with two-hidden layers, and it is trained with datasets from three GNSS observation stations in Thailand. The prediction from the proposed neural network deviates from the baseline reference using the minimum standard deviation method with significantly faster computational time. The trained NN model is also tested for estimating the receiver bias values at other untrained stations in Thailand.
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Equatorial Plasma Bubble Detection using the Convolutional Neural Network (CNN) and Support Vector Machine (SVM)
(2023-01-01)
Thanakulketsarat, Thananphat
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Supnithi, Pornchai
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Myint, Lin Min Min
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Hozumi, Kornyanat
Equatorial plasma bubbles (EPB) refer to the area of low electron density in the Earth's ionosphere near the equator during post sunset and post-midnight. They influence the radio communications and GPS signals. In this work, we study the EPB occurrences and characteristics using the VHF radar images observed at the Chumphon station, Thailand, near the magnetic equator.. We develop an EPB image detection system using a hybrid learning technique with convolutional neural network (CNN) and support vector machine (SVM) and evaluate the accuracy of the proposed CNN-SVM model using two kernels: polynomial kernel and radial basis function (RBF) kernel.
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Comparative Study of the Equatorial Plasma Bubbles using VHF Radar Images and Spatial ROTI Maps at Low-Latitude Region
(2023-01-01)
Tongkasem, Napat
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Myint, Lin M.M.
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Supnithi, Pornchai
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Hozumi, Kornyanat
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Nishioka, Michi
Equatorial Plasma Bubbles (EPBs) depict electron density depletion region originating at the bottom side of the F layer in the ionosphere. The EPBs are often observed in the low latitude region after post-sunset period, particularly, in equinoctial months. Since EPBs have a negative impact on high-precision positioning techniques, degrading convergence time and accuracy, it is essential to study the spatial variations of EPBs during their lifetime. In this work, we develop 2-D temporal-spatial maps based on the rate of change TEC change (ROTI) index analyzed from pseudorange information in a GNSS receiver network over Thailand. The area covers the magnetic equatorial and low-latitude regions including equatorial ionosphere anomaly (EIA). Using 2-D ROTI maps (longitude vs latitude), two types of ROTI keograms (time vs latitude and time vs longitude), we analyze the spatial and temporal changes of recent EPB events. Complementing this analysis, we propose to jointly anlayze the VHF radar images at Prachomklao Chumphon VHF radar station (Lat:10.72 N, Lon: 99.37, Magn. Lat: 1.34). The radar system can scan the ionosphere from geographic latitude 0° N to 20° N and from 140 to 860 km altitude range. The results show that with the three types of data methods, characterizations, speed, velocity and occurrences of EPB are obtained.
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Analysis of local geomagnetic index under the influence of equatorial electrojet (EEJ) at the equatorial Phuket geomagnetic station in Thailand
(2022-09-01)
Myint, Lin M.M.
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Hozumi, Kornyanat
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Saito, Susumu
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Supnithi, Pornchai
The local K-index is an important proxy to monitor geomagnetic disturbances due to the solar wind in space weather study. The diurnal variation of geomagnetic fields observed in the magnetic equatorial region is dominated by the equatorial electrojet (EEJ), and the variation of EEJ is directly related to the local ionospheric dynamics; therefore, in this work, the local K-index is generated by based on the geomagnetic field measurement at an equatorial geomagnetic station in Phuket, Thailand and the effects of EEJ on the computed local K-indices are analyzed. At each station, an L9 (the lower limit for K = 9) value is set to develop a conversion table between the magnetic range scales and K-indices, and that L9 value must be assigned based on the characterization of the geomagnetic variations at that station. In this work, suitable L9 values are determined by analyzing the distributions of the local K-index and the planetary geomagnetic index, Kp-index. According to the results in the present study, the L9 value of 500 nT can provide local K-indices that can classify the geomagnetic disturbances more correctly. The results show that 40% of the local K-index is consistent with the Kp-index, and about 45% of the local K indices are ±1 deviated from Kp-indices. It is found that using the suitable L9 value can partially control the EEJ's dominance on K-index. Moreover, we investigated the seasonal and day-to-day variability of the diurnal variation of the geomagnetic fields from the Phuket station. Upon reviewing the data, the equatorial geomagnetic field variations were consistent with the planetary geomagnetic activity levels, and the day-to-day changes of the daytime field amplitudes were relatively high in the high solar activity year and moderate in the low solar activity year.
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Using Principal Component Analysis of Satellite and Ground Magnetic Data to Model the Equatorial Electrojet and Derive Its Tidal Composition
(2022-09-01)
Soares, Gabriel
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Yamazaki, Yosuke
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Morschhauser, Achim
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Matzka, Jürgen
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Pinheiro, Katia J.
The intensity of the equatorial electrojet (EEJ) shows temporal and spatial variability that is not yet fully understood nor accurately modeled. Atmospheric solar tides are among the main drivers of this variability but determining different tidal components and their respective time series is challenging. It requires good temporal and spatial coverage with observations, which, previously could only be achieved by accumulating data over many years. Here, we propose a new technique for modeling the EEJ based on principal component analysis (PCA) of a hybrid ground-satellite geomagnetic data set. The proposed PCA-based model (PCEEJ) represents the observed EEJ better than the climatological EEJM-2 model, especially when there is good local time separation among the satellites involved. The amplitudes of various solar tidal modes are determined from PCEEJ based tidal equation fitting. This allows to evaluate interannual and intraannual changes of solar tidal signatures in the EEJ. On average, the obtained time series of migrating and nonmigrating tides agree with the average climatology available from earlier work. A comparison of tidal signatures in the EEJ with tides derived from neutral atmosphere temperature observations show a remarkable correlation for nonmigrating tides such as DE3, DE2, DE4, and SW4. The results indicate that it is possible to obtain a meaningful EEJ spectrum related to solar tides for a relatively short time interval of 70 days.
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Neural Network Prediction of Receiver Bias in Ionospheric Delay Computation
(2022-01-01)
Thu, Phyo C.
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Supnithi, Pornchai
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Min Myint, Lin Min
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Saito, Susumu
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Saekow, Apitep
An important measure typically used to understand ionosphere properties and disturbances is total electron content (TEC). A typical approach to calculating the ionospheric TEC is by analyzing dual-frequency GPS data. Satellite and receiver biases are the primary discrepancies in TEC computation. In this work, we develop a neural network to predict the instrumental receiver bias based on slant TEC. The minimum standard deviation method is used to calculate the receiver bias. Neural network with two hidden layers is trained with datasets and then used to predict the receiver bias. The predicted receiver bias from the proposed neural network differs from the baseline method by about 10 to 20 percent.

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