Automatic classification of ionogram with CNN

The ionosphere is an essential part of the near-earth environment. Ionosphere classification, especially the irregularities identification via ionograms in real time has significant meaning in the ionospheric research. In this paper, a method based on CNN is proposed to classify the ionograms automatically. To train the CNN, over 20000 ionograms from Chinese Academy of Sciences Digital Ionosonde installed at Huailai, Wuhan, Hengxian, Ganzi and Xiamen are utilized. A good performance over 83% identification accuracy was achieved by the new method.