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基于Vulkan的电大复杂目标电磁散射SBR计算方法与GPU加速技术

Vulkan-based SBR method for electromagnetic scattering of electrically large and complex targets with GPU acceleration techniques
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摘要 提出了一种基于Vulkan架构的弹跳射线(shooting and bouncing ray,SBR)加速计算方法,用于电大复杂目标雷达散射截面的快速计算。设计了高效的Vulkan计算着色器,充分利用GPU硬件光追,显著提升了SBR法中光线求交的计算速度;引入了双命令缓冲机制,使得CPU与GPU能够高效协同工作,从而加速多角度扫描任务的执行;在虚拟孔径面上划分互不干扰的子任务,进一步提升了多GPU并行的利用效率。实验结果表明:所提出方法在计算电大复杂目标雷达散射截面时相较于FEKO RL-GO方法实现了40倍以上的加速;双命令缓冲机制提升了约42%的多角度扫描速度;双GPU计算并行效率超过90%。 This paper proposes a Vulkan-based acceleration method for shooting and bouncing ray(SBR)to obtain fast computation of the radar cross section(RCS)of complex electrically large targets.An efficient Vulkan compute shader is designed to fully leverage GPU hardware ray tracing,which an significantly improve the ray intersection computation speed for the SBR method.A dual-command-buffer mechanism is introduced to enhance CPU-GPU collaboration for accelerating multi-angle scanning tasks.Additionally,non-interfering sub-tasks are divided on the virtual aperture surface,further improving multi-GPU parallel utilization efficiency.Experimental results demonstrate that the proposed method achieves over 40×acceleration in RCS computation for complex electrically large targets compared to the FEKO RL-GO method.The dual-command-buffer mechanism improves multi-angle scanning speed by approximately 42%,while dual-GPU computation achieves over 90%parallel efficiency.
作者 王思凡 吴扬 贾浩文 胡志明 申子昂 徐若锋 梁达 赵雷 WANG Sifan;WU Yang;JIA Haowen;HU Zhiming;SHEN Ziang;XU Ruofeng;LIANG Da;ZHAO Lei(China University of Mining and Technology,Xuzhou 221116,China;Nanjing University of Aeronautics and Astronautics,Nanjing 210000,China;Research Institute for Special Structures of Aeronautical Composite,Jinan 250023,China)
出处 《电波科学学报》 北大核心 2025年第3期457-463,共7页 Chinese Journal of Radio Science
基金 中国矿业大学中央高校基本科研业务费专项资金(2024-10942) 中国矿业大学研究生创新计划(2024WLKXJ092) 江苏省研究生科研与实践创新计划(KYCX24_2767)。
关键词 雷达散射截面(RCS) 弹跳射线(SBR)法 光线追踪 GPU加速计算 电大复杂目标 radar cross section(RCS) shooting and bouncing rays(SBR) ray tracing GPU accelerated computation large and complex targets
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