基于NVIDIA GPU后向投影FFBP算法的加速研究
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珠海微度芯创科技有限责任公司 珠海 519000

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TN95

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Research on accelerating the backward projection FFBP algorithm based on NVIDIA GPU
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Zhuhai Microcreative Tech. Co.,Ltd., Zhuhai 519000, China

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    摘要:

    后向投影(BP)算法,在计算成像过程中未采用近似,成像质量高,任何阵列构型成像均适合。近年来在雷达成像技术领域广泛应用。但在毫米波三维全息成像中,计算效率较低,影响了实时成像的实现。在三维极坐标条件下,快速因式分解后向投影(FFBP)算法,利用子孔径划分的方式进行成像,一定程度上解决了实时成像的问题。本文利用四线程CPU与GPU加速CUDA平台实现FFBP算法,并对比分析了多点目标成像,结果基本一致,进而验证加速算法的有效性。进一步,通过电磁仿真软件,对分辨力板建模和仿真,模拟真实目标,并进行GPU加速成像,计算时间比四线程CPU提高33.97倍,适用于三维近场实时成像系统,更好的应用于人体安检领域。

    Abstract:

    The Back Projection (BP) algorithm does not use approximation in the imaging calculation process, and the imaging quality is high. Any array configuration is suitable for imaging. In recent years, it has been widely used in the field of radar imaging technology. However, in millimeter wave three-dimension holographic imaging, the computational efficiency is low, which affects the implementation of real-time imaging. Under the conditions of three-dimensional polar coordinates, the Fast Factorization Backward Projection (FFBP) algorithm uses sub-aperture division for imaging, which solves the real-time imaging problem to a certain extent. This article implements the FFBP algorithm based on the four threaded CPU and GPU accelerated CUDA platform, and compares and analyzes the imaging of multi-point targets. The results are basically consistent, thereby verifying the effectiveness of the accelerated algorithm. Furthermore, through electromagnetic simulation software, the resolution board is modeled and simulated to simulate real targets, and GPU accelerated imaging is performed. The calculation time is 33.97 times faster than the four threaded CPU, making it suitable for 3D near-field real-time imaging systems and better applied in the field of human security inspection.

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潘丰,高伟,罗俊,刘文冬,周春元,张慧.基于NVIDIA GPU后向投影FFBP算法的加速研究[J].电子测量技术,2023,46(22):148-152

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  • 在线发布日期: 2024-03-08
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