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High-resolution and high-accuracy  global ionosphere maps estimated by GNSS and LEO constellations: simulative and real data experimental results
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<p>Global ionospheric total electron content (TEC) map has been employed in many high-precision areas. However, its spatial and temporal resolution is not ideal since the ground-based Global Navigation Satellite Systems (GNSS) stations distributed unevenly. Fortunately, many low earth orbit (LEO) satellite constellations will provide a large number of observations that can be used for ionospheric monitoring in the future. In this contribution, we presented two methods, which are the single-layer normalization (SLN) method and the dual-layer superposition (DLS) method, for ionospheric modeling based on the simulative and real data of GNSS+LEO satellites.</p><p>For simulative data, a constellation with 192 LEO satellites is simulated. And then,&#160; the global ionospheric maps (GIMs) are estimated by all Multi-GNSS and simulative LEO satellite observations. The results showed that the root mean square (RMS) is reduced by approximately 25% and 21% for SLN method and DLS method, respectively. For real data,&#160; 20 available scientific LEO satellites, such as Jason-2/3, COSMIC-1/-2, Swarm missions, etc.,&#160; are employed in the ground-based GNSS ionospheric modeling. The results showed that the differences between the ionospheric model estimated by GNSS+LEO and that by GNSS data are mainly over the oceanic region, which may exceed &#177;20 TECU. The improvement of RMS over the oceanic region is about 15% for the ionospheric model estimated by GNSS+LEO. The RMS of the ionospheric model improved approximately 4.0% compared with that by GNSS data using the dSTEC assessment method.</p>
Title: High-resolution and high-accuracy  global ionosphere maps estimated by GNSS and LEO constellations: simulative and real data experimental results
Description:
<p>Global ionospheric total electron content (TEC) map has been employed in many high-precision areas.
However, its spatial and temporal resolution is not ideal since the ground-based Global Navigation Satellite Systems (GNSS) stations distributed unevenly.
Fortunately, many low earth orbit (LEO) satellite constellations will provide a large number of observations that can be used for ionospheric monitoring in the future.
In this contribution, we presented two methods, which are the single-layer normalization (SLN) method and the dual-layer superposition (DLS) method, for ionospheric modeling based on the simulative and real data of GNSS+LEO satellites.
</p><p>For simulative data, a constellation with 192 LEO satellites is simulated.
And then,&#160; the global ionospheric maps (GIMs) are estimated by all Multi-GNSS and simulative LEO satellite observations.
The results showed that the root mean square (RMS) is reduced by approximately 25% and 21% for SLN method and DLS method, respectively.
For real data,&#160; 20 available scientific LEO satellites, such as Jason-2/3, COSMIC-1/-2, Swarm missions, etc.
,&#160; are employed in the ground-based GNSS ionospheric modeling.
The results showed that the differences between the ionospheric model estimated by GNSS+LEO and that by GNSS data are mainly over the oceanic region, which may exceed &#177;20 TECU.
The improvement of RMS over the oceanic region is about 15% for the ionospheric model estimated by GNSS+LEO.
The RMS of the ionospheric model improved approximately 4.
0% compared with that by GNSS data using the dSTEC assessment method.
</p>.
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