基于MapReduce的合成孔径雷达后向投影快速成像方法
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TN958

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国家自然科学基金项目(面上项目,重点项目,重大项目);广西自然科学基金项目;广西科技厅项目;桂林电子科技大学研究生教育创新计划资助项目


A Fast Imaging Method of Synthetic Aperture Radar Back Projection Based on MapReduce
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    摘要:

    针对雷达大场景高分辨率高精度快速成像的应用需求,提出了一种基于MapReduce的合成孔径雷达后向投影快速成像方法,将方位向成像任务划分成若干个成像单元,进行分布式并行化方位向成像计算,最后将所有成像单元的计算结果进行相参累加。该方法对每个脉冲数据标上天线阵元的位置信息,使得各个脉冲数据可以并行补偿相位;采用相等脉冲数划分成一个数据块的方式提高计算效率和实现负载均衡;设置Combiner函数对成像单元内的计算结果进行提前聚合,解决后期聚合时间较长的问题。在Hadoop分布式计算平台下验证了本文方法的有效性,相对于单机计算的后向投影成像方法,基于4个计算节点的本文方法可加速3.7倍,可见该方法满足合成孔径雷达大场景高分辨率高精度快速成像的应用需求。

    Abstract:

    Aiming at the application requirements of fast imaging of large radar scenes, high-resolution and high-precision, a fast imaging method of synthetic aperture radar back projection based on MapReduce is proposed. The azimuth imaging task was divided into several imaging units for distributed parallel computing, and finally reduced the results of all the imaging units by coherent accumulation. The method marked each pulse data with the position information of the antenna array element, so that each pulse data can be compensated the phase in paralleling. The method of dividing the equal number pulses into a data block improved the calculation efficiency and achieved load balancing. The Combiner function was set up to reduce the calculated results in the imaging unit in advance, solving the time-consuming problem in the late stage. The effectiveness of the proposed method is verified by the Hadoop distributed computing platform. Compare with the back projection imaging method of stand-alone computing, the method based on 4 computing nodes can accelerate 3.7 times. It can be seen that the method satisfies the application requirements of fast imaging of large scenes, high-resolution and high-precision of synthetic aperture radar.

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李长树,廖可非,欧阳缮,等. 基于MapReduce的合成孔径雷达后向投影快速成像方法[J]. 科学技术与工程, 2020, 20(11): 4389-4394.
Li Changshu, Liao Kefei, Ou Yangshan, et al. A Fast Imaging Method of Synthetic Aperture Radar Back Projection Based on MapReduce[J]. Science Technology and Engineering,2020,20(11):4389-4394.

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历史
  • 收稿日期:2019-07-23
  • 最后修改日期:2020-01-06
  • 录用日期:2019-10-09
  • 在线发布日期: 2020-05-29
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