The Influence of Space Weather on the Relationship Between the Parameters TEC and foF2 of the Ionosphere

Maltseva, O. A.

doi:10.1109/jrfid.2021.3076227

Cited by 4 publications

(2 citation statements)

References 20 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The data produced by the suite may be used to correct ionospheric models [25] and to estimate the radio-channel ionospheric parameters [26]. Herewith, one should remember that GNSSs have their own limitations for such goals [27].…”

Section: Recovering Tec and Maximum Usable Frequency For Oblique Pathsmentioning

confidence: 99%

“…First, we corrected the IRI-Plas model by the local parameter (by critical frequency). Then, we spread the correction data τ = foF2GNSS/foF2IRI [26] over the entire model. In general, such an approach is a global parameter correction, and, as a target value, we used only one value for the vertical TEC.…”

Section: Recovering Tec and Maximum Usable Frequency For Oblique Pathsmentioning

confidence: 99%

See 1 more Smart Citation

MITIGATOR: GNSS-Based System for Remote Sensing of Ionospheric Absolute Total Electron Content

et al. 2022

View full text Add to dashboard Cite

Monitoring the Earth’s ionosphere is an important, fundamental and applied problem. Global Navigation Satellite Systems (GNSS) provide a way of measuring the ionospheric total electron content (TEC), but real-time single-station absolute TEC measurements are still a problem. This study describes a single-station system to measure the absolute TEC, based on the GNSS – MITIGATOR (MonITorInG the Absolute TOtal electRon content) system. The latter enables real-time measurements for the absolute TEC and its derivatives in time and in space to be obtained. The system is implemented by using JAVAD receivers. The convergence time and the run-mode retention time is ~8 h. We provide potential methods for using the system to estimate the critical frequency of the ionosphere, foF2, at oblique paths in the Siberian region. The developed tool could be useful for supporting real-time multi-instrumental ionosphere monitoring or for compensating for the ionospheric errors of radio equipment.

show abstract

Section: Recovering Tec and Maximum Usable Frequency For Oblique Pathsmentioning

confidence: 99%

Section: Recovering Tec and Maximum Usable Frequency For Oblique Pathsmentioning

confidence: 99%

MITIGATOR: GNSS-Based System for Remote Sensing of Ionospheric Absolute Total Electron Content

et al. 2022

View full text Add to dashboard Cite

show abstract

Analysis of Ionospheric TEC Variations Due to X, M & C Class Solar Flares during the Years 2003 to 2018 and Comparison with IRI Models

Kiruthiga¹,

Mythili

Vijay³

et al. 2022

Geomagn. Aeron.

View full text Add to dashboard Cite

Modeling and Forecasting Ionospheric foF2 Variation in the Low Latitude Region during Low and High Solar Activity Years

Ren

Yin

et al. 2022

Remote Sensing

View full text Add to dashboard Cite

Prediction of ionospheric parameters, such as ionospheric F2 layer critical frequency (foF2) at low latitude regions is of significant interest in understanding ionospheric variation effects on high-frequency communication and global navigation satellite system. Currently, deep learning algorithms have made a striking accomplishment in capturing ionospheric variability. In this paper, we use the state-of-the-art hybrid neural network combined with a quantile mechanism to predict foF2 parameter variations under low and high solar activity years (solar cycle-24) and space weather events. The hybrid neural network is composed of a convolutional neural network (CNN) and bidirectional long short-term memory (BiLSTM), in which CNN and BiLSTM networks extracted spatial and temporal features of ionospheric variation, respectively. The proposed method was trained and tested on 5 years (2009–2014) of ionospheric foF2 observation data from Advanced Digital Ionosonde located in Brisbane, Australia (27°53′S, 152°92′E). It is evident from the results that the proposed model performs better than International Reference Ionosphere 2016 (IRI-2016), long short-term memory (LSTM), and BiLSTM ionospheric prediction models. The proposed model extensively captured the variation in ionospheric foF2 feature, and better predicted it under two significant space weather events (29 September 2011 and 22 July 2012).

show abstract

The Influence of Space Weather on the Relationship Between the Parameters TEC and foF2 of the Ionosphere

Cited by 4 publications

References 20 publications

MITIGATOR: GNSS-Based System for Remote Sensing of Ionospheric Absolute Total Electron Content

MITIGATOR: GNSS-Based System for Remote Sensing of Ionospheric Absolute Total Electron Content

Analysis of Ionospheric TEC Variations Due to X, M & C Class Solar Flares during the Years 2003 to 2018 and Comparison with IRI Models

Modeling and Forecasting Ionospheric foF2 Variation in the Low Latitude Region during Low and High Solar Activity Years

Contact Info

Product

Resources

About