A new hybrid ionospheric tomography algorithm by combining ground-based GNSS and ionosonde data

Computerized ionospheric tomography(CIT) is one of the most important means to obtain the three-dimensional structure of the ionosphere in a wide range of regions. In view of the deficiency of using ground-based GNSS for ionospheric 3D tomography alone, a new hybrid ionospheric tomography algorithm by combining ground-based GNSS and ionosonde data is proposed. The algorithm combines the advantages of high vertical resolution of ionosphere detected by ionosonde and high horizontal resolution of ground-based GNSS CIT. The updated IRI model by ionosonde data is used as the background ionospheric model, and then the improved ART algorithm combined with ground-based GNSS TEC is used for tomography. Based on the data of IGS, the crustal movement observation network of China (CMONOC) and GIRO ionosonde, the three-dimensional ionospheric tomography of China and its surrounding areas is realized. Madrigal TEC data and independent ionosonde data in China are used to evaluate the TEC and electron density obtained by tomography. The results of TEC accuracy evaluation show that the TEC average error and standard deviation of CIT algorithm are significantly lower than those of IRI model and CODE GIM data. The electron density evaluation results show that only relying on the ground-based GNSS for CIT can improve the accuracy of f_oF₂ but can not effectively improve the accuracy of h_mF₂; after combining the ionosonde data, the reconstruction accuracy of ionospheric f_oF₂ and h_mF₂ is significantly improved, in which the average error and standard deviation of h_mF₂ decreases from 20.6 km and 16.5 km to 14.8 km and 11.7 km, and the ionosonde data play a significant role in improving the vertical resolution of CIT.