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首页> 外文期刊>IEEE Transactions on Antennas and Propagation >Efficiency Enhancement of the Characteristic Basis Function Method for Modeling Forest Scattering Using the Adaptive Cross Approximation Algorithm
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Efficiency Enhancement of the Characteristic Basis Function Method for Modeling Forest Scattering Using the Adaptive Cross Approximation Algorithm

机译:基于自适应交叉近似算法的森林散射特征量基函数方法的效率增强

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摘要

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 Zc 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.
机译:本交流讨论了在森林环境中的散射问题的3-D建模背景下,特征基函数方法(CBFM-E)的扩展版本与自适应交叉逼近(ACA)算法的混合。生成精简矩阵时将应用ACA,以改善与此步骤相关的CPU时间。评估了由这种杂交产生的CBFM解决方案的性能增强,并且研究了天然林场景的几何形状和异质性对使用ACA算法获得的增益以及解决方案准确性的影响。我们表明,混合CBFM-E / ACA方法使我们能够显着减少计算缩减矩阵Zc所需的CPU时间,而不会影响解决方案的准确性。此外,增强技术的效率既不受散射体的介电对比度的影响,也不受网格用于说明森林场景异质性的不均匀性的影响。

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