:: Volume 9, Issue 4 (3-2022) ::
jgit 2022, 9(4): 87-107 Back to browse issues page
The Improvement of IRI2016 global maps by the integration of Swarm and GPS observations
Sedigheh Karimi, Mohammad Ali Sharifi *, Saeed Farzaneh
University of Tehran
Abstract:   (565 Views)
This paper presents a model, the International Reference Model 2016 (IRI), in order to improve the vertical total electron content (VTEC) maps by combining Swarm observations with global positioning system (GPS) ones. The proposed model consists of two parts: the background model and the corrections. In this paper, the IRI2016 model was selected as the background model and the corrections were modeled by spherical harmonic expansion functions up to the degree and rank 15 in a Sun-fixed reference frame. In the combination of VTECs derived from Swarm and GPS, the systematic biases of Swarm satellites are considered as unknown constant parameters in each epoch of modeling. Besides, in order to take the different accuracy levels of observational groups into consideration, the Helmert variance component estimation method is used. To evaluate the proposed model, the two-dimensional combined global ionosphere maps (GIMs) are constructed on the 28th  of  September 2017 and the 3rd  of January 2018 with 7 and 1 kp-indices values, respectively. The comparison of the combined GIM maps with the International GNSS Service (IGS) GIM maps, shows that the combined model is more compatible with IGS maps, and adding Swarm and GPS observations to the IRI2016 background model can significantly improve the IRI2016 model, especially in oceanic regions. The results show that the root mean square (RMS) and root mean square error (RMSE) maps are decreased about 19% to 45% and 43% to 67% for the day with high Kp-index and about 13% to 40% and 15% to 43% for the day with low kp-index, respectively.
Keywords: Total electron content (TEC), Swarm, GPS, IRI-2016 model, variance component estimation
Full-Text [PDF 2248 kb]   (124 Downloads)    
Type of Study: Research | Subject: Geodesy
Received: 2021/11/19 | Accepted: 2022/02/23 | ePublished ahead of print: 2022/02/23 | Published: 2022/03/7



XML   Persian Abstract   Print



Rights and permissions
Creative Commons License This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
Volume 9, Issue 4 (3-2022) Back to browse issues page