基于CUDA的SAR成像R-D算法并行优化研究

2018 10th International Conference on Communication Software and Networks (ICCSN) Pub Date : 2018-07-01 DOI:10.1109/iccsn.2018.8488250

Pei Wei, Jing Du, Sai Sui, Yancang Chen

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引用次数: 0

摘要

合成孔径雷达(SAR)成像技术广泛应用于遥感观测、导航定位等领域，具有数据规模大、工作时间长等特点。基于CUDA编程模型，设计并实现了基于CPU-GPU异构平台的SAR成像R-D算法并行优化，并在GPU Tesla K20上进行了测试。实验表明，R-D算法的核心步骤的效率得到了很大的提高。

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The Research on Parallel Optimization of SAR Imaging R-D Algorithm Based on CUDA

Synthetic Aperture Radar (SAR) imaging technology is widely used in the field of remote sensing observation, navigation positioning and so on, SAR imaging is large in data scale and long in operating time. Based on the Compute Unified Device Architecture (CUDA) programming model, the SAR imaging R-D algorithm is designed and implemented for parallel optimization on the CPU-GPU heterogeneous platform and tested on the GPU Tesla K20. The test shows that the efficiency of the core steps of R-D algorithm has been greatly improved.

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2018 10th International Conference on Communication Software and Networks (ICCSN)

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