Ionospheric Remote Sensing Using MF Radio Signals and Software-Defined Radio

Abstract

The ionosphere is a region of the upper atmosphere, ranging from about 60 km to 1000 km above ground, consisting of free electrons and ions primarily due to solar radiation. Because of its charged nature, it is essential for long-distance radio communication, navigation, and space weather monitoring. The ionosphere changes constantly, and its variability can significantly affect radio wave propagation. As a result, there is ongoing interest in developing tools for observing ionospheric disturbances. Radio signals at frequencies of 30 MHz and below are reflected by the lower ionosphere and are commonly used for ionospheric remote sensing through both active and passive techniques. However, the medium-frequency (MF, 0.3-3 MHz) band remains relatively underutilized. In particular, commercial AM (amplitude modulation) radio transmitters operating between 530 and 1700 kHz offer several advantages, despite not being designed for scientific purposes. These transmitters are widely distributed across geographic regions and continuously broadcast radio waves, making them valuable sources for passive ionospheric remote sensing with broad spatial coverage.The aim of this dissertation is to explore the use of AM radio signals for detecting ionospheric disturbances during both nighttime and daytime, using a low-cost software-defined radio (SDR)-based receiver developed specifically for this work. The receiver supports dual-channel data acquisition with time synchronization across multiple receivers. Real-time monitoring of ionospheric conditions is enabled through a developed real-time data processing program, which also reduces data storage requirements and makes long-term measurements more feasible.To estimate the virtual reflection height of nighttime skywaves, a new approach is proposed that computes the audio delay between groundwave and skywave signals using synchronized recordings from distributed receivers. This method relies solely on AM radio signals and does not require pulsed transmissions or ionospheric modeling tools. It is capable of tracking virtual height variations with time resolution on the order of seconds and distinguishing between reflections from the E and F layers, providing a foundation for detecting more detailed variations within different ionospheric layers during nighttime.For nighttime measurements, we observed numerous Doppler shifts associated with gravity waves propagating in the ionosphere. The virtual height estimation method helped identify distinct gravity wave characteristics in different layers, with slower, larger variations in the F layer and faster, smaller variations in the E layer. Traveling ionospheric disturbances (TIDs) were detected and quantified through phase analysis using data acquired by three distributed remote receivers. Spread features in both the E and F layers were also detected, showing associations with gravity waves that are consistent with previous findings using HF Doppler sounding. Measurements during solar terminators revealed clear, layer-dependent responses to sunrise and sunset transitions.Finally, the nighttime measurement techniques were adapted for daytime experiments, which present greater challenges primarily due to strong absorption from the D layer. By comparing received signal amplitudes with predicted groundwave amplitudes from an ITU-R (International Telecommunication Union Radiocommunication Sector) model, we confirmed that skywave components become increasingly dominant beyond 500 km and can be reliably detected beyond 1000 km. Daytime measurements revealed a variety of ionospheric disturbances, including MF signal blackout effects with the presence of increased solar activity, daytime gravity waves, and temporary reductions in plasma density associated with the 2024 total solar eclipse.