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Characterizing Ionospheric Effects on GNSS Reflectometry at Grazing Angles from Space.

Authors :
Moreno, Mario
Semmling, Maximilian
Stienne, Georges
Hoque, Mainul
Wickert, Jens
Source :
Remote Sensing; Oct2023, Vol. 15 Issue 20, p5049, 19p
Publication Year :
2023

Abstract

Coherent observations in GNSS reflectometry are prominent in regions with smooth reflecting surfaces and at grazing elevation angles. However, within these lower elevation ranges, GNSS signals traverse a more extensive atmospheric path, and increased ionospheric effects (e.g., delay biases) are expected. These biases can be mitigated by employing dual-frequency receivers or models tailored for single-frequency receivers. In preparation for the single-frequency GNSS-R ESA "PRETTY" mission, this study aims to characterize ionospheric effects under variable parameter conditions: elevation angles in the grazing range (5° to 30°), latitude-dependent regions (north, tropic, south) and diurnal changes (day and nighttime). The investigation employs simulations using orbit data from Spire Global Inc.'s Lemur-2 CubeSat constellation at the solar minimum (F10.7 index at 75) on March, 2021. Changes towards higher solar activity are accounted for with an additional scenario (F10.7 index at 180) on March, 2023. The electron density associated with each reflection event is determined using the Neustrelitz Electron Density Model (NEDM2020) and the NeQuick 2 model. The results from periods of low solar activity reveal fluctuations of up to approximately 300 TECUs in slant total electron content, 19 m in relative ionospheric delay for the GPS L1 frequency, 2 Hz in Doppler shifts, and variations in the peak electron density height ranging from 215 to 330 km. Sea surface height uncertainty associated with ionospheric model-based corrections in group delay altimetric inversion can reach a standard deviation at the meter level. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
20724292
Volume :
15
Issue :
20
Database :
Complementary Index
Journal :
Remote Sensing
Publication Type :
Academic Journal
Accession number :
173338023
Full Text :
https://doi.org/10.3390/rs15205049