Oral Presentation

Using two-dimensional autocorrelation method to improve the performance of automatic algorithm on ionogram

Author(s): Kai-Jun Ke, Yen-Hsyang Chu and Ching-Lun Su (Graduate Institute of Space Science and Engineering, NCU)

Presenter: Kai-Jun Ke (Graduate Institute of Space Science and Engineering, National Central University)

A new ionosonde is under construction at Chung-Li VHF radar station on the campus of National Central University in Taiwan. We develop our own data processing algorithm to automatically retrieve ionospheric parameters of different sublayers from observed ionogram traces in nearly real time. In addition to the conventional image analysis technique, we use two-dimensional autocorrelation function to identify and separate the ordinary (O-) wave from extraordinary (X-) wave traces for further analysis. A comparison between ionospheric parameters retrieved from the automatic processing algorithm developed in this study and those obtained from manually scaling ionograms shows that the use of two-dimensional autocorrelation function combined with image analysis can achieve reliable and accurate ionospheric parameters.