An Automatic CADI’s Ionogram Scaling Software Tool for Large Ionograms Data Analytics

T Venkateswara Rao,D Venkata Ratnam,M Sridhar

doi:10.1109/access.2022.3153470

T Venkateswara Rao, D Venkata Ratnam + Show 1 more

Open Access

https://doi.org/10.1109/access.2022.3153470

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Abstract

Scale the ionosonde ionograms to produce accurate readings is a professional manual scaling technique. However, there is a high demand for auto-scaling software that can manage a large number of ionograms in order to avoid the time and effort involved in manual scaling as well as human errors. Noise-free, accurate trace identification and precise segmentation are required for the auto-scaling program to work. The Canadian Advanced Digital Ionosonde (CADI) ionograms are processed and auto-scaled using a new model on an open-source (Python) platform in this paper. Filtering the noise, Convolution Neural Network (CNN) based trace detection, layer-wise segmentation, and then extracting the ionospheric features are used to accomplish the scaling accuracy. The investigation uses raw ionogram files generated by the CADI system in Hyderabad, India (Lat: <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$17.47^{\circ }\text{N}$ </tex-math></inline-formula> , Long: <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$78.57^{\circ }\text{E}$ </tex-math></inline-formula> ) between 2014 and 2015. Raw ionograms in <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$^\ast $ </tex-math></inline-formula> .md4 or <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$^\ast $ </tex-math></inline-formula> .md2 file formats can be accepted by the suggested model (Individual or Hourly integrated). The proposed auto-scaling software tool’s individual block performance is examined with several classes of ionograms, and the overall performance is evaluated with a huge set of ionograms obtained during adverse space weather circumstances (16th to 18th March 2015). Univap Digital Ionosonde Data Analysis (UDIDA) software tool was considered for manual scaling. The results of manual scaling are compared with that of proposed scaling software. In fmin and h’f, respectively, the proposed model has a mean absolute error (MAE) of 0.36 MHz and 11.72 km, and a root mean square error (RMSE) of 0.7 MHz and 22.36 km.

Highlights

Digital ionosondes are high frequency (HF) and high-power ionosphere probing devices
RESULTS & DISCUSSION Raw ionogram files (*.md4) generated by Canadian Advanced Digital Ionosonde (CADI) located at Hyderabad, India (Lat: 17.47°N, Long: 78.57°E) during 2014 – 2015 are considered
About 78840 valid ionograms are available for analysis and manually constructed the classification data set with about 40,000 ionograms

Summary

Introduction

Digital ionosondes are high frequency (HF) and high-power ionosphere probing devices. Ionosonde transmits series of modulated pulses at vertical incidence and records reflected echoes representing the ionospheric features in the form of ionograms. Traces in the ionogram reveal the features of the ionosphere in terms of frequency and height components. The ionospheric features can be extracted from the ionogram by employing manual scaling or auto-scaling software tools. Even though the manual scaling results are accurate, but it is achieved only with the right expertise. Manual scaling of various classes of ionograms is a time taking and tedious job. The ionogram auto-scaling is faster and entirely accurate than manual scaling values but tends to fail in complexity, such as ordinary and extraordinary traces, E and

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