Automatic detection of ionospheric Alfvén resonances using signal and image processing techniques

Abstract

Induction coils permit the measurement of small and very rapid changes of the magnetic field. A new set of induction coils in the UK (at L = 3.2) record magnetic field changes over an effective frequency range of 0.1–40 Hz, encompassing phenomena such as the Schumann resonances, magnetospheric pulsations and ionospheric Alfvén resonances (IARs). The IARs typically manifest themselves as a series of spectral resonance structures (SRSs) within the 1–10 Hz frequency range, usually appearing as fine bands or fringes in spectrogram plots and occurring almost daily during local night-time, disappearing during the daylight hours. The behaviour of the occurrence in frequency (f) and the difference in frequency between fringes (Δf) varies throughout the year. In order to quantify the daily, seasonal and annual changes of the SRSs, we developed a new method based on signal and image processing techniques to identify the fringes and to quantify the values of f, Δf and other relevant parameters in the data set. The technique is relatively robust to noise though requires tuning of threshold parameters. We analyse 18 months of induction coil data to demonstrate the utility of the method.