Efficiency Enhancement of the Characteristic Basis Function Method for Modeling Forest Scattering Using the Adaptive Cross Approximation Algorithm

This communication discusses the hybridization of the extended version of the characteristic basis function method (CBFM-E) with the adaptive cross approximation (ACA) algorithm in the context of 3-D modeling of the problem of scattering from a forest environment. The ACA is applied when generating the reduced matrix to improve the CPU time associated with this step. The performance enhancement of the CBFM solution resulting from this hybridization is evaluated, and the impact of the geometry and heterogeneity of a natural forest scene on the gain achieved via the use of the ACA algorithm and on the accuracy of the solution is studied. We show that the hybrid CBFM-E/ACA approach enables us to significantly reduce the CPU time needed to compute the reduced matrix Z
^c
without compromising the accuracy of the solution. Furthermore, the efficiency of the enhancement technique is not affected either by the dielectric contrasts of the scatterers or by the nonuniformity of the mesh that it is used to account for the heterogeneity of the forest scene.