Deep learning for global ionospheric TEC forecasting: Different approaches and validation X Ren, P Yang, H Liu, J Chen, W Liu Space Weather 20 (5), e2021SW003011, 2022 | 58 | 2022 |
Global ionospheric TEC forecasting for geomagnetic storm time using a deep learning‐based multi‐model ensemble method X Ren, P Yang, D Mei, H Liu, G Xu, Y Dong Space Weather 21 (3), e2022SW003231, 2023 | 23 | 2023 |
Topside ionosphere of NeQuick2 and IRI‐2016 validated by using onboard GPS observations from multiple LEO satellites X Ren, J Chen, X Zhang, P Yang Journal of Geophysical Research: Space Physics 125 (9), e2020JA027999, 2020 | 10 | 2020 |
Investigating the Effects of Ionospheric Scintillation on Multi‐Frequency BDS‐2/BDS‐3 Signals at Low Latitudes H Liu, X Ren, X Zhang, D Mei, P Yang Space Weather 21 (6), e2022SW003362, 2023 | 8 | 2023 |
The short-term prediction of low-latitude ionospheric irregularities leveraging a hybrid ensemble model H Liu, P Yang, X Ren, D Mei, X Le, X Zhang, M Freeshah IEEE Transactions on Geoscience and Remote Sensing 62, 1-15, 2024 | 6 | 2024 |
Global ionosphere modeling based on GNSS, satellite altimetry, radio occultation, and DORIS data considering ionospheric variation J Chen, X Ren, P Yang, G Xu, L Huang, S Xiong, X Zhang Journal of Geophysical Research: Space Physics 128 (10), e2023JA031514, 2023 | 6 | 2023 |
Leveraging the CYGNSS Spaceborne GNSS‐R Observations to Detect Ionospheric Irregularities Over the Oceans: Method and Verification X Ren, H Liu, D Mei, P Yang, Z Zhang, M Freeshah, X Zhang Space Weather 20 (11), e2022SW003141, 2022 | 6 | 2022 |
Evaluation and validation of various rapid GNSS global ionospheric maps over one solar cycle H Liu, D Mei, G Xu, P Yang, X Ren, X Zhang Advances in Space Research 70 (8), 2494-2505, 2022 | 6 | 2022 |
Method and validation of real‐time global ionosphere modeling constraint by multi‐source GNSS/LEO data J Chen, X Ren, G Xu, P Yang, H Liu, X Zhang Space Weather 22 (4), e2023SW003800, 2024 | | 2024 |