Published in Advances in Space Research, 2019
With the Nequick model as the initial field of the Kalman-filter(KF) algorithm, the global ionospheric density field was constructed by KF algorithm, and the subsequent works were processed.
Recommended citation: Fu, N.; Guo, P.; Wu, M.; Huang, Y.; Hu, X.; Hong, Z. Simulating and Assimilating Ionospheric Observations with Multisources. Advances in Space Research 2019.
Published in Remote Sens., 2019
This study introduced a Kalman filtering assimilation model that considers the DCB errors of GPS/LEO satellites and GNSS stations. The assimilation results and reliability were verified by various types of data, such as ionMap, ionosonde, ISR, and the EDP of ionPrf from COSMIC.
Recommended citation: Fu, N.; Guo, P.; Wu, M.; Huang, Y.; Hu, X.; Hong, Z. The Two-Parts Step-by-Step Ionospheric Assimilation Based on Ground-Based/Spaceborne Observations and Its Verification. Remote Sens. 2019, 11, 1172. https://www.mdpi.com/2072-4292/11/10/1172
Published in RemoteSensingScience, 2016
By statistics of the retrieval temperature and humidity, we found: the existing satellite clock stability and the LEO satellite orbit determination accuracy meet the needs of the occultation inversion.
Recommended citation: Fu N. F., Guo P., Wu M.J., etal. Retrieval Processing Technique For LEO-LEO Radio Occultation Atmospheric Data and Error Sources Analysis [J]. RemoteSensingScience, 2016, 4(2): 51 - 64. http://www.ivypub.org/RSS/download/33584.shtml