Journal Article

A New Method for Reconstruction of Regional Three‐Dimensional Electron Density Distributions Using AI‐Based Data Assimilation Method and Incoherent Scatter Radar Measurements

Ren, Ganming, Fang, Hanxian, Huang, Hongtao, Cao, Xiaoqun, Li, Chenghao, Xiao, Chao, Duan, Die, Cai, Yihui, Lin, Yang

2024

Overview

The ionosphere's dynamic structure affects electromagnetic radiation by altering radio wave propagation, impacting daily communications. The characteristics of the ionosphere are primarily characterized by electron density parameters. This paper proposes a method to construct Three‐Dimensional (3‐D) electron density distributions with arbitrary spatiotemporal resolution in ISR observational regions. The method, termed Artificial Intelligence‐based data assimilation (AI‐Assim), integrates data assimilation directly into a neural network. It assimilates electron density from the IRI‐2020 model to fill ISR observation gaps. Experiments conducted using the Sanya Incoherent Scatter Radar (SYISR) in Hainan, China, successfully constructed a 3‐D electron density structure over the region, with a 0.2° latitude/longitude resolution and 1 km height resolution. The method's effectiveness was validated by calculating the mean square error and comparing the results with digisonde measurements. Plain Language Summary This study leverages the most powerful ionospheric observation tool, the ISR, to construct 3‐D electron density distributions with arbitrary spatial resolution. Relying solely on empirical models often leads to accuracy issues, while 3‐D electron density models based purely on observational methods typically suffer from low resolution. All observational methods encounter difficulties in achieving continuous, high spatial resolution monitoring of the entire sky, and ISR is one of the most effective techniques available. However, even with interpolation methods, the coverage area of ISR remains limited. Therefore, this study explores a method that uses the neural network to assimilate electron density values from the IRI‐2020 model, aiming to fill the gaps in ISR detection. By assimilating International Reference Ionosphere values to approximate observed values, the accuracy of the 3‐D electron density results is enhanced. Multiple iterations of AI‐ Assim enable the construction of 3‐D electron density distributions with arbitrary spatial resolution. Key Points We developed a method for constructing 3‐D electron density distributions with arbitrary spatiotemporal resolution at ISR stations The method termed AI‐Assim, continuously assimilating electron density from the IRI‐2020 model to fill ISR observation gaps Experiments using SYISR data achieved a 3‐D electron density model with 0.2° map resolution and 1 km height resolution

• Publisher: John Wiley & Sons, Inc
• Subject: Accuracy / AI‐based data assimilation / arbitrary spatiotemporal resolution / Artificial intelligence / Data assimilation / Data collection / digisonde / Effectiveness / Electromagnetic radiation / Electron density / Electrons / Empirical models / Incoherent scatter radar / Interpolation / Interpolation methods / Ionosphere / Ionospheric propagation / Neural networks / Radar / Radar data / Radar measurement / Radiation measurement / Radio wave propagation / Radio waves / Sanya regional / Scatter propagation / Scattering / Spatial discrimination / Spatial resolution / Wave propagation