3385

GPU-Based Shooting and Bouncing Ray Method for Fast RCS Prediction

Yubo Tao, Hai Lin, Hujun Bao
State Key Lab. of CAD&CG, Zhejiang Univ., Hangzhou, China
IEEE Transactions on Antennas and Propagation, 2010, Volume 58, Issue 2, p.494-502

@article{tao2010gpu,

   title={GPU-based shooting and bouncing ray method for fast RCS prediction},

   author={Tao, Y. and Lin, H. and Bao, H.},

   journal={Antennas and Propagation, IEEE Transactions on},

   volume={58},

   number={2},

   pages={494–502},

   issn={0018-926X},

   year={2010},

   publisher={IEEE}

}

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The shooting and bouncing ray (SBR) method is highly effective in the radar cross section (RCS) prediction. For electrically large and complex targets, computing scattered fields is still time-consuming in many applications like range profile and ISAR simulation. In this paper, we propose a GPU-based SBR that is fully implemented on the graphics processing unit (GPU). Based on the stackless kd-tree traversal algorithm, the ray tube tracing can rapidly evaluate the exit position in a single pass on the GPU. We also present a technique for fast electromagnetic computing that allows the geometric optics (GO) and Physical optics (PO) integral to be carried out on the GPU efficiently during the ray tube tracing. Numerical experiments demonstrate that the GPU-based SBR can significantly improve the computational efficiency of the RCS prediction, about 30 times faster, while providing the same accuracy as the CPU-based SBR.
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