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FAST RCS PREDICTION USING MULTIRESOLUTION SHOOTING AND BOUNCING RAY METHOD ON THE GPU
Author(s) -
Peng Cheng Gao,
Yu-Bo Tao,
Hai Lin
Publication year - 2010
Publication title -
electromagnetic waves
Language(s) - English
Resource type - Journals
eISSN - 1559-8985
pISSN - 1070-4698
DOI - 10.2528/pier10061807
Subject(s) - computer science , grid , tree traversal , computational science , acceleration , intersection (aeronautics) , algorithm , massively parallel , quadtree , multiresolution analysis , tree (set theory) , parallel computing , k d tree , artificial intelligence , mathematics , physics , geometry , wavelet , wavelet transform , aerospace engineering , mathematical analysis , discrete wavelet transform , classical mechanics , engineering
This paper presents a GPU-based multiresolution shooting and bouncing ray (MSBR) method with the kd-tree acceleration structure for the fast radar cross section (RCS) prediction of electrically large and complex targets. The multiresolution grid algorithm can greatly reduce the total number of ray tubes, as it adaptively adjusts the density of ray tubes for regions with difierent complexities of their structures, while the kd-tree acceleration structure can highly decrease the number of ray-patch intersection tests. The multiresolution grid technique and kd-tree traversal algorithm are fully implemented on the GPU to further accelerate the SBR by exploiting the massively parallel computing ability. Numerical experiments demonstrate that the proposed GPU-based MSBR can signiflcantly improve the computational e-ciency. It is about 40 times faster than the CPU MSBR, and at least 4.8 times faster than the GPU-based SBR without the multiresolution grid algorithm.

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