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Bistatic Coherent Scattering From Rough Soils With Application to GNSS Reflectometry.

Authors :
Comite, Davide
Ticconi, Francesca
Dente, Laura
Guerriero, Leila
Pierdicca, Nazzareno
Source :
IEEE Transactions on Geoscience & Remote Sensing. Jan2020, Vol. 58 Issue 1, p612-625. 14p.
Publication Year :
2020

Abstract

We present and discuss an electromagnetic model for the description of the coherent scattering from bare soils illuminated by a radar system under arbitrary bistatic geometries. The scattering problem is solved under the Kirchhoff approximation (KA) accounting for both the sphericity of the wavefront of the incident wave and the radiation pattern of the transmitting and receiving antennas. We propose here a general formulation and solution of the scattering problem applicable to an arbitrary bistatic geometry. We discuss and demonstrate the importance of our extension for the characterization of the coherent scattering generated in bistatic radar systems, both inside and outside the plane of incidence. The model is validated against the numerical solution of the Kirchhoff integral and, in the case of the perfect plane conductor, by comparison with the image theory. The work is intended to provide a simple methodology to characterize the coherent normalized radar cross section (NRCS) of a rough surface to be used within the radar equation for extended targets, similarly to what is done for the incoherent component. It aims at enabling a local characterization of the coherent scattering in realistic conditions (e.g., in the presence of inhomogeneous and mountainous surfaces), a feature that is particularly important for practical applications, such as the modeling and understanding of the bistatic scattering generated by sources of opportunity and specifically for Global Navigation Satellite System Reflectometry (GNSS-R) related applications. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
01962892
Volume :
58
Issue :
1
Database :
Academic Search Index
Journal :
IEEE Transactions on Geoscience & Remote Sensing
Publication Type :
Academic Journal
Accession number :
143317160
Full Text :
https://doi.org/10.1109/TGRS.2019.2938442