基于MapReduce的合成孔径雷达压缩感知成像分布式计算方法

2020 IEEE 3rd International Conference on Electronic Information and Communication Technology (ICEICT) Pub Date : 2020-11-13 DOI:10.1109/ICEICT51264.2020.9334375

Can Zheng, Kefei Liao, Shan Ouyan, Changshu Li

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引用次数: 0

摘要

在合成孔径雷达(SAR)成像中使用压缩感知方法存在两个主要问题:计算时间长和t计算能力的可扩展性不足。为了解决上述问题，本文提出了一种基于MapReduce的SAR压缩感知成像分布式成像方法。首先对稀疏数据进行标记，然后通过两次MapReduce计算重建距离和方位角图像。利用并行计算的优势，实现了SAR压缩遥感成像的加速。

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Distributed Computing method for Synthetic Aperture Radar Compressed Sensing Imaging based on MapReduce

When using the compressed sensing method in Synthetic Aperture Radar(SAR) imaging, there are two major problems: long calculation time and insufficient scalability of t calculation ability. In order to solve the above problems, this paper proposes a distributed imaging method for SAR compressed sensing imaging based on MapReduce. First, the sparse data is labeled, then the range and azimuth image are reconstructed by two MapReduce calculation processes. With parallel computing advantages, the acceleration of SAR compressed sensing imaging is realized.

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2020 IEEE 3rd International Conference on Electronic Information and Communication Technology (ICEICT)

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