Title :
Monte Carlo simulations of scattering of electromagnetic waves from dense distributions of nonspherical particles
Author :
Tsang, Leung ; Ding, K.H. ; Shih, S.E.
Author_Institution :
Dept. of Electr. Eng., Washington Univ., Seattle, WA, USA
Abstract :
In a dense, discrete random medium, the propagation and scattering of waves are not only affected by the individual properties of the particles such as sizes, shapes and permittivities, but also by the group properties such as the statistics of relative particle positions and relative orientations. In this paper, the authors investigate the interactions of electromagnetic waves with a dense medium consisting of spheroidal particles with random or aligned orientations. A multiple scattering formulation based on the volume integral equation and method of moments is developed. A shuffling process is used to generate the positions of densely packed spheroids within a cubic box. The scattering results are averaged over many realizations. Numerical results are presented for the extinction rates to illustrate the polarimetric scattering properties and the differences of scattering properties between nonspherical and spherical particles
Keywords :
Monte Carlo methods; backscatter; electromagnetic wave scattering; geophysical techniques; method of moments; radar cross-sections; remote sensing by radar; terrestrial electricity; EM wave scattering; Monte Carlo simulation; aligned orientation; dense distribution; electromagnetic wave; geology; geophysical measurement technique; group properties; land surface; method of moments; multiple scattering formulation; nonspherical particles; radar remote sensing; radar scattering; random medium; relative orientation; relative particle positions; shuffling process; spheroidal particle; terrain mapping; terrestrial electricity; volume integral equation; Electromagnetic propagation; Electromagnetic scattering; Integral equations; Laboratories; Moment methods; Particle scattering; Permittivity; Shape; Snow; Statistics;
Conference_Titel :
Geoscience and Remote Sensing, 1997. IGARSS '97. Remote Sensing - A Scientific Vision for Sustainable Development., 1997 IEEE International
Print_ISBN :
0-7803-3836-7
DOI :
10.1109/IGARSS.1997.615298