A Method in Determining Ionospheric Total Electron Content Using GNSS Data for non-IGS Receiver Stations

Mendoza, Merlin M.; Juadines, Kyle Ezekiel S.; Macalalad, Ernest P.; Hsiao, Tung‐Yuan

doi:10.1109/iconspace.2019.8905958

Cited by 3 publications

(3 citation statements)

References 8 publications

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“…It is a measure of the number of electrons along a path through which signals are transmitted. TEC can also be mathematically defined as the line integral of the electron density, 𝑁 𝑒, along the path, 𝑙 [5].…”

Section: Introductionmentioning

confidence: 99%

“…These can be estimated along the radio signal's path between the satellite and ground-based receivers. The time delay in the trans-ionospheric signals can also be obtained by the difference in the signal parameters from the two frequencies [5]. Since satellite and navigation systems highly rely on electron densities, the variability of which that is also coincident with the ionizing radiation due to solar flares can be measured.…”

Section: Introductionmentioning

confidence: 99%

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Effects of strong solar flares on the ionospheric electron density over the Philippines

Domingo,

Macalalad

2024

J. Phys.: Conf. Ser.

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Solar flares are capable of generating extreme amounts of ionizing radiation which affects Earth’s atmosphere. These are examined most notably in the X-ray and EUV regimes. The eruption of strong solar flares of classes X6.9, X2.25, and M9.7 were recorded, during which the Philippines was on Earth’s sunlit side. In this paper, the observation of the effects of solar radiation on the ionospheric electron density is done by quantifying the change in the slant total electron content (ΔSTEC). This was calculated by finding the difference between the difference relative STEC and its fitted data. The data were acquired from two GNSS receiver stations (PIMO & PTGG) in the Philippines. Moreover, it was inferred that changes in the electron density are manifest during increased EUV enhancements on the occurrences of the X6.9 and M9.7 flares. The calculated ΔSTEC ranged from ∼0.43 – 0.67 TECU during the X6.9 (PIMO) and ∼0.45 – 0.71 TECU during the M9.7 (PTGG) flares. This signifies that the contribution of the EUV radiation to the ionospheric response in the E and F ionospheric regions is more immense than that of the X-ray.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Effects of strong solar flares on the ionospheric electron density over the Philippines

Domingo,

Macalalad

2024

J. Phys.: Conf. Ser.

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“…Ionospheric sounding is conducted by using the standard techniques of ground-based ionosondes and a network of Global Positioning System (GPS) receivers, which provide high temporal resolution. Ionosondes can measure the vertical profiles of electron density from the ground up to the maximum of the F2 layer [ 7 ], while the GPS receivers can provide the Slant Total Electron Content (STEC) by estimating the signal delay from the satellites to ground-based receivers [ 8 ]. Unfortunately, the coverage of these standard instruments is not sufficient in the Taiwan–Korea region mainly because the instruments can not be installed in the sea.…”

Section: Introductionmentioning

confidence: 99%

Recovery of Ionospheric Signals Using Fully Convolutional DenseNet and Its Challenges

Mendoza

Дмитриев

et al. 2021

Sensors

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The technique of active ionospheric sounding by ionosondes requires sophisticated methods for the recovery of experimental data on ionograms. In this work, we applied an advanced algorithm of deep learning for the identification and classification of signals from different ionospheric layers. We collected a dataset of 6131 manually labeled ionograms acquired from low-latitude ionosondes in Taiwan. In the ionograms, we distinguished 11 different classes of the signals according to their ionospheric layers. We developed an artificial neural network, FC-DenseNet24, based on the FC-DenseNet convolutional neural network. We also developed a double-filtering algorithm to reduce incorrectly classified signals. That made it possible to successfully recover the sporadic E layer and the F2 layer from highly noise-contaminated ionograms whose mean signal-to-noise ratio was low, SNR = 1.43. The Intersection over Union (IoU) of the recovery of these two signal classes was greater than 0.6, which was higher than the previous models reported. We also identified three factors that can lower the recovery accuracy: (1) smaller statistics of samples; (2) mixing and overlapping of different signals; (3) the compact shape of signals.

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Two-Dimensional Mapping of Ionospheric Total Electron Content over the Philippines Using Kriging Interpolation

Maglambayan

Macalalad

2022

Atmosphere

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Monitoring of ionospheric total electron content (TEC) was made possible with the help of satellite data, albeit in one dimension. However, ionospheric TEC maps can be produced from a collection of one-dimensional satellite data over a geographic area. Multiple mapping methods have been recognized; however, this study tried to test one of those methods: kriging interpolation. An algorithm was developed and used to reconstruct GIMs. The optimum number of stations and the semivariogram model were evaluated using GIM maps modeling 12 days of March 2015, accounting for different ionospheric conditions. This includes days of high scintillation and an ionospheric storm due to the St. Patrick’s Day geomagnetic storm of 2015. It was found that 12 stations and the linear semivariogram model had the least mean error in 5 days and had the least standard deviation in 7 days, making it the optimum parameter set. This optimum set was then used to map and analyze the ionosphere using actual satellite data from the Philippine Active Geodetic Network (PAGeNet). From this, it was observed that there is a north–south gradient in VTEC in the region during the day. The VTEC in the north reaches more than 100 TECU, and, in the south, generally around 60–90 TECU depending on the ionospheric condition. VTEC was at a minimum during the night when the VTEC level decreases to around 10 TECU.

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A Method in Determining Ionospheric Total Electron Content Using GNSS Data for non-IGS Receiver Stations

Cited by 3 publications

References 8 publications

Effects of strong solar flares on the ionospheric electron density over the Philippines

Effects of strong solar flares on the ionospheric electron density over the Philippines

Recovery of Ionospheric Signals Using Fully Convolutional DenseNet and Its Challenges

Two-Dimensional Mapping of Ionospheric Total Electron Content over the Philippines Using Kriging Interpolation

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