Clustering and data reduction algorithm applied to spectra measured with a multi-static HF sounding system in Peru

Abstract

The HF radar is a network of HF radio beacons and receivers for ionospheric sounding, and it has been operating in Peru since 2016. The purpose of this instrument is to measure the group delay, Doppler shift, power, and other parameters in order to estimate the regional plasma density as a function of space and time. This information is crucial for forecasting the occurrence of Spread-F. To improve the quality of the spectral data, two changes were made. The first one involved transmitting frequencies separated by 3.3 Hz in each transmission station, which allowed to spectrally separate and identify the signals coming from a given station, displacing the cross-talk in frequency but not eliminating it. Therefore, the second change was made, which corresponds to the development of an algorithm that extracts only the signals of interest from the measured spectrum. It is capable of detecting clusters of data in the spectra classifying them as coherent echoes, while noise sectors are discarded. The algorithm procedure and the comparisons of the spectra and final data are shown in this work.