Inequality Constraints Algorithm to Improve the High Latitudes GNSS Ionosphere Modeling Accuracy
Abstract Due to uneven distribution of the international GNSS service (IGS) organization tracking stations in high latitudes, the observation data used for ionospheric fitting modeling are uneven and incomplete, leading to inadequate modeling accuracy of the total ionospheric content in this region. When the ionospheric fit model is established using observation data from these IGS tracking stations, the grid output values of the ionospheric fitting model contain a large number of negative and zero values, which are contrary to the actual physical meaning of the ionosphere. Aiming at this problem, we adopt the ionospheric grid output negative point, zero point to join inequality constraint conditions, and the inequality constraint least square method, to calculate parameters of optimization. Experimental results show that the algorithm shows a significant improvement in reducing the large number of zeros and negative values in the sparse high-latitude areas, and modeling accuracy of the global ionosphere model is also improved.
Key words :
IGS
global ionosphere model
TEC
high-latitude areas
inequality constraint
Cite this article:
HUANG Xiaodong,TU Rui,LIU Jinhai et al. Inequality Constraints Algorithm to Improve the High Latitudes GNSS Ionosphere Modeling Accuracy[J]. jgg, 2019, 39(7): 722-727.
HUANG Xiaodong,TU Rui,LIU Jinhai et al. Inequality Constraints Algorithm to Improve the High Latitudes GNSS Ionosphere Modeling Accuracy[J]. jgg, 2019, 39(7): 722-727.
URL:
http://www.jgg09.com/EN/ OR http://www.jgg09.com/EN/Y2019/V39/I7/722
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