A penalized motion detection model for extracting ionospheric echoes from low signal-to-noise ratio Ionogram video images

Abstract

Measuring the altitude distribution of electron density in the upper atmosphere, known as the ionosphere, using High-Frequency radio wave reflections often causes the low signal-to-noise ratio of ionospheric echoes due to radio frequency interference. We propose a model for converting low-signal-to-noise-ratio ionospheric echo video images (Ionogram) into noise-reduced images using image processing techniques, for tracing the ionospheric echoes from Ionogram. The proposed method consists of three processing parts: noise removal optimized for individual Ionogram images, extraction of ionospheric echoes by penalized background subtraction technique, and fine-tuning of ionospheric echo signals using a minimum spanning tree algorithm. The proposed model successfully reproduces fine Ionograms with 98% recall and 99% precision.