Myint, Lin Min

Preferred name

Myint, Lin Min

Alternative Name

Myint, L. M.

Myint, L.

Myint, Lin Min Min

Myint, Lin M.

Main Affiliation

School of Engineering

linminmin.my@kmitl.ac.th

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Equatorial Plasma Bubble Detection by Support Vector Machine at Chumphon Station, Thailand
(2022-01-01)
Thanakulketsarat, Thananphat
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Supnithi, Pornchai
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Myint, Lin Min Min
;
Hozumi, Kornyanat
Equatorial Plasma Bubble (EPB) is a phenomenon in which depletion of plasma density occurs in the ionosphere particularly in the equatorial region. It can degrade the performances of the navigation system and satellite communication. In this work, we analyze EPB based on the very-high frequency (VHF) radar images at Chumphon station, Thailand. Then an EPB detection system using the support vector machine (SVM) technique is developed, and the accuracies of the systems using different kernels: linear kernel, the polynomial kernel, the radial basic functions kernel (RBF), and the sigmoid kernel are compared. Among the different kernels, we find that the RBF kernel gives the highest accuracy in prediction at 86.67 percent.
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A TMR mitigation method with 3-track data detection for multi-track multi-head BPMR system
(2017-08-10)
Warisarn, C.
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Busyatras, W.
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Myint, L. M.
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Koonkarnkhai, S.
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Kovintavewat, P.
An off-track situation from misalignment between the center of read head and that of target track is also known as track mis-registration (TMR), which is one of major problems in bit-patterned media recording (BPMR), especially at high areal density (AD) [1-4].
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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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Investigating the F2-layer peak height of IRI-2016 model at the equatorial station during the deepest solar activity for 70 years ago
(2023-01-01)
Jamjareegulgarn, Punyawi
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Taugtragoonpaisan, Udomsit
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Myint, Lin Min Min
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Supnithi, Pornchai
The paper investigates the F2-layer peak height (hmF2) of IRI-2016 model at Sao Luis on the magnetic Equator in 2019. Since the deepest solar activity occurred surprisingly in year 2019 for 70 years ago, hence, the IRI-2016 model prediction should be investigated to know the anomalous ionosphere and the deviations between the observation and IRI prediction. The hmF2 is selected to be studied in this work. Our studied results show that the observed hmF2 and the three hmF2 models of IRI-2016 prediction generally show the similar variations only about 60% during this deepest solar activity and the variations of the four kinds of studied hmF2 values show the similar trends for all seasons, except June solstice. The diurnal variation of hmF2_Giro show three peaks for December solstice months and the equinoctial months, while they show four peaks amazingly in June solstice. The hmF2_SHU is the best option that can agree reasonably well to the observed hmF2 at Sao Luis, excluding the pre-sunrise hmF2 peak for all seasons and a very deep trough in June solstice.
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Single-track equalization method with TMR correction system based on cross correlation functions for a patterned media recording system
(2017-01-01)
Myint, Lin Min Min
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Warisarn, Chanon
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Busyatras, Wiparat
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Kovintavewat, Piya
Bit-patterned media recording (BPMR) is a promising technology for ultra-high density media, however, there are some challenges that need to be addressed including two-dimensional (2D) interference, and track mis-registration (TMR). The system can experience TMR due to misalignment of the head and the track center. Conventionally, TMR is tackled using a servo system in which the head position offset is estimated by processing the overhead servo sequences before reading the data sequences. However, TMR impairment can also occur when the head is reading data sequences that are beyond the servo mechanism. To address this problem, we proposed TMR detection and correction techniques based on our previous work involving a single-track equalization method for a BPMR system using cross-correlation functions between the single readback signal and each of the training sequences from three adjacent tracks. In this proposed technique, the presence and level of TMR is detected and estimated based on the changes in the value of mean square error (MSE) between the equalized and feedback signals from the detectors after passing through a one-dimensional (1D) target for each sequence. Then, the estimated TMR levels are used in selecting the appropriate equalizer and the generalized partial response (GPR) target pair to tackle the TMR from the readback signal. The simulation results show improvement in the data recovery of a BPMR system using the proposed method when the system is experiencing 2D interference and TMR impairment.
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Deep learning-based prediction models for the vertical total electron content using GNSS satellite observations
(2026-08-01)
Mutasov, Gleb
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Myint, Lin Min Min
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Budtho, Jirapoom
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Perwitasari, Septi
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Nishioka, Michi
Ionospheric Total Electron Content (TEC) is a crucial parameter for characterizing the state of the ionosphere and assessing its impact on satellite-based navigation systems and on communication technologies. In equatorial and low-latitude regions, ionospheric irregularities, particularly equatorial plasma bubbles (EPBs), pose significant challenges for satellite navigation and communication due to their capacity to cause rapid TEC fluctuations and signal degradation. Since these effects are especially pronounced during ionospheric and geomagnetic disturbances, making accurate TEC prediction is an essential task for improving the reliability of GNSS-based positioning and space weather applications. This study presents a machine learning-based framework for one-day-ahead prediction of TEC with a 30-min resolution over the magnetic equator and low-latitude regions, with a focus on Southeast Asia. Unlike global models, our approach is tailored to local GNSS observations and directly predicts TEC values along specific satellite-receiver paths, defined by geographic location and satellite visibility. We integrate ionospheric pierce point (IPP) coordinates, geomagnetic indices, and solar activity indicators as features to enhance temporal and spatial forecasting accuracy. To address the nonlinear and nonstationary nature of TEC variations, we investigate and compare three deep learning architectures: a Transformer-based time-series model, a Temporal Kolmogorov–Arnold Network (TKAN), and a Long Short-Term Memory (LSTM). Additionally, the predictions are benchmarked against the empirical IRI-2020 model and a persistence baseline. The results demonstrate that both the Transformer and TKAN models outperform the LSTM and empirical approaches, particularly during different geomagnetic and ionospheric conditions, showing improved robustness and generalization. The proposed framework highlights the potential for accurate, resource-efficient TEC prediction in low-latitude regions and opens a pathway for further improvements by integrating multi-GNSS observations and additional space weather parameters.
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Estimation and Validation of Vertical Total Electron Content Using Standalone Single-Frequency Observations
(2022-01-01)
Tongkasem, Napat
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Myint, Lin Min Min
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Supnithi, Pornchai
Nonuniform ionospheric delay is a well-known cause of degradations in radio wave propagations such as in satellite communication and positioning. In general, the ionospheric delay can be estimated using the Global Navigation Satellite System (GNSS) data from dual or multiple-frequency receivers; however, satellite differential code biases (DCBs) must be downloaded via network connection. For positioning based on standalone single-frequency receivers, the Klobuchar model, a well-known model in the GPS positioning system, is used to estimate the ionospheric delay based on solar activity, season, or region by using the eight coefficients in the broadcast navigation message. Although this model can reduce positioning errors by about 50 percent, the low-latitude disturbances such as the equatorial plasma bubble (EPB) phenomenon, significantly diminishes the accuracy of modeled delay estimation. In this work, we propose an ionospheric delay estimation technique based on observed single-frequency GPS data without requiring network-based corrections for DCB. The ionospheric delays estimated by the proposed method are compared with those from the GPS dual-frequency observation, the broadcast/network models in 2014 (high solar activity) and 2020 (low solar activity). According to the results, the proposed ionospheric delay estimation can correct the ionosphere errors better than the well-known Klobuchar model, by about 9.98 percent and 6.77 percent in 2014 and 2020, respectively. The proposed model increases the ionospheric error correction efficiency in vertical positioning by up to 81 percent in 2014 and 79 percent in 2020.
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Sidetrack data estimation using multi-track joint 2-D viterbi detector in bit patterned media storage
(2018-07-02)
Myint, Lin Min Min
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Supnithi, Pornchai
In the high areal density, bit patterned media recording (BPMR) system, the inter-track interference (ITI) effects become severe when the areal density is increased. In the literature, a multi-track joint 2-D detector with the aid of a multi-reader array technology is proposed to mitigate the ITI effect in BPMR systems because of its significant performance gains achieved by processing the multiple readback signals concurrently. In practice, the multi-track joint 2-D detector can estimate the recorded data from not only the detecting tracks, but also the sidetracks when the ITI effect is considerably high. Although the estimates of the data on the sidetracks are not as good as those on the detecting tracks, they can be applied in or improved by further coding process. In this work, we study the performance of a multi-track joint 2-D Viterbi detector for estimating the data on the sidetracks by adjusting the offset position of heads in the multi-head multi-track (MHMT) BPMR system. The detector recovers the recorded data on the detecting and sidetracks by processing the readback signals from the detecting tracks. We also investigate the performance changes due to the head offsets. The results show that the performance of detector for estimating the data on the sidetracks can be improved by adjusting the head offsets well.
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A study of equatorial plasma bubble structure using VHF radar and GNSS scintillations over the low-latitude regions
(2022-10-01)
Bumrungkit, Acharaporn
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Supnithi, Pornchai
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Saito, Susumu
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Myint, Lin Min Min
Ionospheric irregularities can cause detrimental effects on the global navigation satellite system (GNSS) signals, often in the form of rapid fluctuations in both amplitude and phase. Over the low-latitude regions, the equatorial plasma bubble (EPB) frequently arises after sunset, leading to GNSS scintillations since the signals propagate through ionospheric irregularities. The relationship between amplitude ionospheric scintillations (S4 index) on GNSS signals and EPB characteristics is presented. We investigate the geometrical relationship between backscatter echoes associated with the EPB and the multi-constellation and multi-frequency scintillations, specifically, GPS and Galileo constellations with L1/E1 and L5/E5a signals. By analyzing the GNSS scintillations along the GNSS signal paths, the GNSS ionospheric pierce points (IPPs) are mapped with S4 index at different altitudes and projected along the magnetic field line together with the backscatter echoes at the equatorial atmosphere radar (EAR), West Sumatra, Indonesia. Our results are obtained for moderate scintillation cases due to limited data available for this study. The results show the EPB impact ionospheric scintillations. The S4 index on the L5/E5a signal is more susceptible to scintillations than the L1/E1 signal. Moreover, we found a high correlation between EAR backscatter echoes and S4 values on both L1/E1 and L5/E5a at an altitude between 250 and 350 km, indicating that the EPB occurs on the bottomside of the ionosphere.
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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.

Myint, Lin Min

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