Abstract

Improving the measurement accuracy is a necessary condition for sea surface altimetry using the Global Navigation Satellite System Reflectometry (GNSS-R). The ionosphere and troposphere delay the transmission of satellite signals, which directly affect the measuring accuracy. The influence of the atmospheric environment on GNSS-R altimetry differs from different platforms. By analyzing and sorting out the altimetry data of airborne and spaceborne platforms, this paper studies the variation law of signal delay in the altimetry process from the point of view of mathematical geometry, which provides an example for improving the precision of GNSS-R altimetry measurements. Firstly, in order to facilitate data analysis, this paper constructed an altimetry model with the GNSS satellite position, specular reflection point position, receiver position as nodes, classified direct signals, and reflected signals. Secondly, calculate ionospheric puncture point coordinates , and interpolate GIM products provided by IGS using time and puncture point coordinates to obtain the VTEC value in the vertical direction of the puncture point, which was converted into the path direction STEC by projection function, the ionospheric delay of each part was obtained in this way. The tropospheric delay of each part is considered for the along-path component and the geometric component, the delay of along-path component was calculated by the UNB3m model, and the delay of geometric component was calculated by the equation provided by Nikolaidou (Nikolaidou et al., 2021). Thirdly, by comparing the sea surface height inversion results with or without atmospheric delay correction with the mean sea surface height provided by DTU15, the measurement accuracy with atmospheric delay correction is obviously improved. The study results of the influence of atmospheric delay on the altimetry experiments precision error of airborne and spaceborne platforms show that the error magnitude is consistent with the existing literature. In the airborne experiment, the influence of the ionosphere is negligible and the troposphere has sub-meter influence on altimetry results, among which the tropospheric along-path delay component occupies a high proportion. The geometric delay component has a high correlation with the satellite elevation angle and its influence on the measurement accuracy decreases with the elevation angle increase. The effect of this factor can be effectively weakened by setting a high satellite cutoff angle. In the spaceborne experiment, the effect of atmospheric delay on altimetry results fluctuates in the range of 3∼5 m when the satellite elevation angle is greater than 60°. In this paper, the method of calculating signal atmospheric delay through geometric relation to improving the measurement accuracy can provide an example for the atmospheric delay correction of GNSS-R ocean altimetry with high precision and spatial resolution in future research.

Highlights

  • Sea surface height (SSH) is the basic data for the study of ocean dynamics, meteorology, geodesy, geophysics, geodesy, and other fields

  • The results showed that GNSS dual-frequency or multi-frequency signals could be used to estimate the ionospheric delay by Global Navigation Satellite System Reflectometry (GNSS-R) technology and the dual-frequency pseudo-distance measurement and model prediction could be used to obtain the result that the measurement accuracy of 2 m could be improved after 1s integration

  • We studied the process of the GNSS-R SSH measurement of atmospheric delay influence on measuring precision, and the VTEC at the ionospheric puncture point is obtained by interpolating the GIM production which is provided from IGS, which is converted into the path direction STEC through the projection function

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Summary

Introduction

Sea surface height (SSH) is the basic data for the study of ocean dynamics, meteorology, geodesy, geophysics, geodesy, and other fields. The famous Jason-2 altimeter satellite is jointly developed by CNES, NASA, EUMETSAT and NOAA, which can achieve the measurement of centimeter-level of SSH. It plays a huge role in weather forecasting and climate monitoring but its revisiting period is 9.9156 days and its coverage is concentrated in the sea, due to its lack of mesoscale spatial resolution results in that the surface water information at this scale cannot be observed steadily for a long time and cannot meet the application requirements of new ocean observation (Ren et al, 2018; Liu et al, 2019; Liu, 2020)

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