Abstract

The Global Positioning System (GPS) reflected signal has been demonstrated to remotely sense the oceans, land surfaces and the cryosphere, including measuring snow depth, soil moisture, vegetation growth and wind direction. Since the Earth surface’s characteristics are very complex, the surface reflectivity process and interaction with GPS signals is not well understood. In this study, we investigate the surface’s reflectivity and variability of snow and ice surfaces interacting with GPS L1 and L2 signals in order to retrieve multipath signals and infer surface characteristics by using the direct and reflected polarizations of each signal. Firstly, the effects of both GPS satellite elevation angle and GPS receiver’s antenna height variations on the multipath signal variability have been investigated by numerical formulations. Secondly, the specular reflection coefficients’ features and the total surface polarization for liquid and solid surfaces are discussed. Moreover, the linear polarization and circular polarizations (co-polarized and cross-polarized) as well as their corresponding convolution functions are developed horizontally and vertically. The results show that the multipath signals are more sensitive to the satellite elevation angle variations than to changes in the GPS receiver’s antenna height. The convolution function demonstrates that the snowy surface has a minimum reflectance in circular polarization but maximum reflectance in linear polarization. GPS signals reflecting from an ice-covered surface show a maximum value in circular polarization reflectance and a minimum for linear polarization reflectance. Moreover, the values for reflection from soils are between those for snow and ice in all polarization types. The placement of soil surface reflectance values between snowy and icy surface ones may be noteworthy in new remote sensing applications.

Highlights

  • Nowadays, Global Positioning System (GPS) reflectometry and scatterometry have incredible applications in the field of theEarth system sciences as new remote sensing tools in oceanography, hydrology and glaciology [1,2].GPS reflectometry provides a way to infer the surface properties remotely because the reflectance spectra at radio wavelengths contain properties about the surface compositions [3,4,5]

  • We generally deal with GPS scattered and reflected signals; but in physical reflectivity, we ignore the chemical characteristics of the surface and we only concentrate on the surface’s physical status, such as the variations related to its physical shape rather than the material features

  • Thereafter, the variability of multipath signatures subjected to the changes in satellite elevation angle itself (Vɛ) and the variability of multipath signatures subjected to the GPS antenna height variations (VH) can be analyzed in the different H values

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Summary

Introduction

GPS reflectometry and scatterometry have incredible applications in the field of the. Litvinov et al [8] investigated the reflection properties of soil and vegetation surfaces by using airborne data to model the total and polarized reflectances in the unique form for both soil and vegetation surfaces. They performed their experiments with airborne data instead of ground GPS reflected signals. The reaction of snow, ice and soil surface to GPS scattered L1 and L2 signals, characteristically including the specular reflection, total surface reflectivity, the linear polarization and. Snow and ice-covered surfaces play important roles in environmental systems, especially hydrologic cycles and climate change, and it is worthwhile to focus on them

Theory and Methodology
Physical Reflectivity
Reflectance Characteristic
Surface Reflectance Characteristic for Linear and Circular Polarization
Convolution Functions for Surface Reflectance Characteristics
GPS Reflected Signals and Physical Reflectivity
GPS Reflected Signals Surface and Reflectance Characteristics
Conclusions

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