Parallelized multilevel Characteristic Basis Function method applied to scattering model for forest remote sensing.

A parallelized version of multilevel Characteristic Basis Function method (ML-CBFM) is applied in this paper to the problem of electromagnetic scattering in the VHF and UHF bands from trees in large forest areas that are modeled as three dimensional, finite-length, dielectric cylinders. The use of this method enables us to achieve a significant reduction in terms of computing time and memory consumption, as compared to the conventional Method of Moments (MoM), and this, in turn, enables us to handle very large forest areas, well beyond the reach of conventional MoM. Furthermore, we take advantage of the fact that the ML-CBFM algorithm is naturally parallelizable, which provides us an added advantage over the conventional MoM. The ML-CBFM results are shown to be in good agreement with those obtained via the conventional MoM, which confirms the fact that the proposed method is not only computationally efficient, but is accurate as well. [ABSTRACT FROM PUBLISHER]