Time-frequency analysis of VLF for seismic-ionospheric precursor detection: Evaluation of Zhao-Atlas-Marks and Hilbert-Huang Transforms

This work investigates the application of two post-processing methods of extracting spectra from VLF signals in order to detect disturbances that could be attributed to seismic-ionospheric precursory phenomena. Although precursory phenomena have been investigated in detail in past studies, a different application of time-frequency analysis methods may produce distinct patterns, which reveal disturbances in the VLF spectra received from stations that are in the propagation path over preparation zones, and also pinpoint disturbances that could be attributed to seismic-ionospheric precursors. To this purpose, three different methods of post processing are compared. These are the Wavelet Transform as a benchmark method in the form of the Continuous Wavelet Transform, a noise-assisted variant of the Hilbert-Huang Transform and the Zhao-Atlas-Marks Distribution. Comparative diagrams are presented and the advantages and weaknesses of each method are presented.