A New Algorithm for High-Quality Ionogram Generation and Analysis

Abstract

Standard digital ionograms that are generated by fast Fourier transform or autoregressive modeling suffer from high interference levels due to other users of the HF channel which produce artifacts and distortion, hence complicating automatic processing and information extraction. In this paper, a new method is proposed to obtain high-quality ionograms of the desired layer reflections and automatically extract important information such as critical frequencies. Following the standard procedures, two sets of periodograms are obtained by using rectangular and Blackman windows. These two periodograms are filtered and fused utilizing an automatic edge-detection-based time-frequency detector. The fused ionogram provides sharp description of the layer reflections with very low sidelobe structure (ringing). The performance of this new ionogram algorithm is tested using chirp sounder data collected from an oblique midlatitude path. It is observed that the presented algorithm is highly successful in obtaining robust and sharp ionograms free of artifacts. Furthermore, a new algorithm is proposed for automated computation of dispersion and critical frequencies of the magnetoionic components detected on the ionogram. Since efficient signal-processing algorithms are utilized, the proposed method can be implemented in real time.