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IEEE Transactions on Antennas and Propagation
Volume 47 Number 5, May 1999

Low Grazing Incidence Millimeter-Wave Scattering Models and Measurements for Various Road Surfaces

Page 851.

Abstract:

Systematic characterization of the scattering behavior of traffic targets, clutter, and their associated interactions are required in order to design and assess the performance of millimeter-wave-based sensors for automated highway system (AHS) applications. In this paper, the polarimetric radar backscatter response of various road surfaces is investigated both theoretically and experimentally. In general, it is found that the overall scattering response of road surfaces is composed of volume and surface scattering components. Recently a hybrid volume scattering model was developed for predicting the backscatter response of smooth asphalt surfaces at millimeter-wave frequencies. There, only the volume scattering was accounted for, however, experimental results show that the surface scattering cannot be ignored when the surface roughness parameters become comparable to the radar wavelength. In this paper, the previous study is extended to include the radar backscatter response of concrete surfaces, snow-covered smooth surfaces, and rough asphalt or concrete surfaces. Radiative transfer (RT) theory is used to model the volume scattering and the integral equation model is used to describe the surface scattering. Asphalt and concrete mixtures are dense random media whose extinction and phase matrices are characterized experimentally. Ice and water over asphalt and concrete surfaces are modeled by homogeneous layers. Fresh snow is modeled by a sparse random medium whose extinction and phase matrices are obtained analytically. The University of Michigan 94-GHz polarimetric radar system was used to perform polarimetric backscatter measurements of the aforementioned road surfaces at near grazing incidence angles (70°-88°). Comparison of the measured and theoretically predicted backscattering coefficients and polarimetric phase difference statistics shows excellent agreement.

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