Complementing regional ground GNSS-STEC computerized ionospheric tomography (CIT) with ionosonde data assimilation

A near-real-time computerized ionospheric tomography (CIT) technique was developed over the East Asian sector to specify the 3-D electron density field. The technique is based on a plethora of Global Navigation Satellite System observables within the region of interest which is bounded horizontally 110°–160°E and 10°–60°N and extending from 80 to 25,000 km in altitude. Prior to deployment, studies validated the CIT results using ionosonde, middle-upper atmosphere radar and occultation data and found the technique to adequately reconstruct the regional ionosphere vertical structure. However, with room for improvement in estimating the peak height and avoiding physically unrealistic negative densities in the final solution, we present preliminary results from a technique that addresses these issues by incorporating CIT results into a data assimilation (DA) technique. The DA technique adds ionosonde bottomside measurements into CIT results, thereby improving the accuracy of the reconstructed bottomside 3-D structure. More specifically, on average CIT NmF2 and hmF2 improve by more than 60%. Further, during analysis, ionospheric electron densities are assumed to be better described by probability log-normal distribution, which introduces the positivity constraint that is mandatory in ionospheric imaging.

Adaptive Smoothness Constraint Ionospheric Tomography Algorithm

Ionospheric tomography reconstruction based on global navigation satellite system observations is usually an ill-posed problem. To resolve it, an adaptive smoothness constraint ionospheric tomography algorithm is proposed in this work. The new algorithm performs an adaptive adjustment for the constrained weight coefficients of the tomography system. The computational efficiency and the reconstructed quality of ionospheric imaging are improved by using the new algorithm. A numerical simulation experiment was conducted in order to validate the feasibility and superiority of the algorithm. The statistical results of the reconstructed errors and the comparisons of ionospheric profiles confirmed the superiority of the new algorithm. Finally, the new algorithm was successfully applied to reconstruct three-dimensional ionospheric images under geomagnetic quiet and geomagnetic disturbance conditions over Hunan province. The tomographic results are reasonable and consistent with the general behavior of the ionosphere. The positive and negative phase storm effects are found during geomagnetic storm occurrence.

REVIEW OF TOMOGRAPHIC RECONSTRUCTION METHODS OF THE IONOSPHERE USING GNSS

ABSTRACT. Spatial and temporal variation of the electron density in the atmosphere makes the ionosphere a difficult region to model. A major difficulty arises due to the incomplete geometrical coverage of the Global Navigation Satellite System (GNSS) for tomographic applications, making the ionospheric tomographic system an ill-conditioned problem. Although the tomographic system is ill-conditioned, several techniques have been developed to partially overcome the problem. There is great interest in using tomographic techniques for ionospheric imaging, because it allows describing the ionosphere in terms of electron density, which is an important parameter for studying the behavior of the physical processes that occur in the upper atmosphere. In Brazil, there are additional interests in the tomographic techniques, due to the peculiar characteristics of the ionosphere and of the geomagnetic field over the region. In this direction, methods of ionospheric tomographic reconstruction are presented and discussed in this review. Particular emphasis is given to the mathematical formulation from grid-based and function-based methods and are presented some of their main advantages and limitations.Keywords: TEC, Inverse Problem, Grid-Based Tomography, Function-Based Tomography, Ionospheric Imaging. RESUMO. A variação espaço-temporal da densidade eletrônica na atmosfera terrestre torna a ionosfera uma região de difícil modelagem. A principal dificuldade no imageamento da ionosfera com o GNSS (Global Navigation Satellite System ) é devido à geometria dos satélites, pois torna o sistema tomográfico mal condicionado. Muito embora a geometria não permita solução direta do sistema, diversas técnicas foram desenvolvidas para parcialmente superar tal problema. Há grande interesse no uso de técnicas de tomografia para o imageamento da ionosfera, pois permitem descrever a ionosfera ao nível da densidade eletrônica, sendo este um importante parâmetro para compreender os processos físicos que ocorrem na alta atmosfera. No Brasil, existem interesses adicionais no imageamento ionosférico por meio de técnicas tomográficas devido às características peculiares da ionosfera e do campo geomagnético sobre a região. Neste sentido, métodos utilizados para a reconstrução tomográfica da ionosfera são apresentados e discutidos nesta revisão. Uma ênfase especial é dada para a formulação matemática dos métodos baseados em células e em funções, além da apresentação de algumas de suas principais vantagens e limitações.Palavras-chave: TEC, Problema Inverso, Tomografia Baseada em Células, Tomografia Baseada em Funções, Imageamento Ionosférico.