Title :
Polarimetric scattering from two-layered two-dimensional random rough surfaces with and without buried objects
Author :
El-Shenawee, Magda
Author_Institution :
Dept. of Electr. Eng., Univ. of Arkansas, Fayetteville, AR, USA
Abstract :
A three-dimensional polarimetric analysis of the two-layered rough ground with and without buried objects is investigated here. A rigorous electromagnetic surface integral-equation-based model is used in this analysis. The statistical average of the polarimetric scattering matrix elements is computed based on the Monte Carlo simulations for both the vertically and horizontally polarized incident waves. The results show a significant impact on the scattered intensities due to the two-layer nature of the ground. However, these intensities show almost no difference between the ground signature with or without the object. On the other hand, the statistical average of the covariance matrix elements shows a distinct difference between these two signatures despite the small size of the buried object.
Keywords :
Monte Carlo methods; buried object detection; data acquisition; electromagnetic wave polarisation; electromagnetic wave scattering; geophysical techniques; ground penetrating radar; integral equations; polarimetry; remote sensing by radar; Monte Carlo simulations; buried objects; computational electromagnetics; covariance matrix elements; ground signature; horizontally polarized incident waves; integral-equation-based model; multilayered rough ground; polarimetric scattering matrix elements; rigorous electromagnetic surface; rough surface scattering; scattered intensities; statistical average; three-dimensional polarimetric analysis; two-layered rough ground; two-layered two-dimensional random rough surfaces; vertically polarized incident waves; Buried object detection; Covariance matrix; Dielectrics; Electromagnetic analysis; Electromagnetic interference; Electromagnetic modeling; Electromagnetic scattering; Electromagnetic wave polarization; Rough surfaces; Surface roughness;
Journal_Title :
Geoscience and Remote Sensing, IEEE Transactions on
DOI :
10.1109/TGRS.2003.815675