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Updated: Jun 26, 2026

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Algorithms and Resources for the Monitoring of Very-Low-Frequency Signal Deviations Due to Solar Activity Using a

Ilia Iliev1, Kostadin Tudjarov1, Ivaylo Nachev1

  • 1Faculty of Telecommunications, Technical University of Sofia, 1000 Sofia, Bulgaria.

Sensors (Basel, Switzerland)
|July 27, 2024
PubMed
Summary

This study developed a web-based software-defined radio (SDR) system for detecting solar activity. Combining multiple SDRs significantly improved accuracy, achieving over 98% correlation for solar flare events.

Keywords:
D-regionSDRSIDVLFionospheremonitoring systemradio astronomysoftware-defined radiosolar activity monitoringsolar flarevery-low-frequency signals

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Area of Science:

  • Space Physics
  • Radio Science
  • Geophysics

Background:

  • Solar activity, including solar flares and coronal mass ejections, impacts Earth's space environment.
  • Understanding these effects is crucial for predicting space weather events like geomagnetic storms.
  • Investigating the influence of solar activity on radio signal propagation, particularly very-low-frequency (VLF) signals, is an active area of research.

Purpose of the Study:

  • To develop and test an experimental web-based software-defined radio (SDR) monitoring system for indirect solar activity detection.
  • To assess the system's capability in estimating and potentially predicting space weather events.
  • To investigate the effect of solar activity on VLF signal propagation.

Main Methods:

  • Development of a distributed SDR monitoring network.
  • Comparison of data from the SDR system with established sources like the GOES satellite and Dunksin SuperSID system.
  • Utilization of Pearson correlation coefficients to analyze data.
  • Combining signal-to-noise ratios from multiple SDRs to enhance results.

Main Results:

  • The SDR monitoring system demonstrated high accuracy in detecting solar activity.
  • Correlation values exceeding 90% were observed between the SDR system and GOES/Dunksin data during solar flares.
  • Combining signal-to-noise ratios from multiple SDRs further improved accuracy, yielding correlations above 98%.

Conclusions:

  • The developed web-based SDR system is effective for indirect solar activity detection and monitoring.
  • Combining data from spatially distributed SDRs significantly enhances measurement accuracy and solar event identification.
  • The system shows promise for investigating solar activity's impact on VLF signal propagation and predicting space weather events.