基于GPU并行计算的雷达杂波模拟研究  

Research on Radar Clutter Simulation Based on GPU Parallel Computing

作　　者：徐国伟 陈建[1] 成怡 XU Guowei;CHEN Jian;CHENG Yi(School of Electrical Engineering and Automation,Tiangong University,Tianjin 300387,China;Tianjin Key Laboratory of Advanced Electrical Engineering and Energy Technology,Tiangong University,Tianjin 300387,China)

机构地区：[1]天津工业大学电气工程与自动化学院,天津300387 [2]天津工业大学天津市电工电能新技术重点实验室,天津300387

出　　处：《计算机工程》2020年第11期306-314,共9页Computer Engineering

基　　金：天津市自然科学基金(17JCYBJC18500,17JCYBJC19400,18JCYBJC88400,18JCYBJC88300)。

摘　　要：现代雷达杂波模拟需使用杂波数据实时分析与处理回波信号,然而传统球不变随机过程(SIRP)方法生成杂波数据耗时较长。通过对SIRP方法进行改进,提出一种利用图形处理器(GPU)并行计算提升杂波生成实时性的方法。在计算统一设备架构(CUDA)下,对相关相干K分布杂波算法进行多任务串-并行分析,采用cuBLAS库对细粒度卷积计算进行优化,利用OpenMP+CUDA多任务调度机制改进粗粒度任务并行计算,以提高CPU-GPU利用率并减少数据等待时间。实验结果表明,该方法生成杂波数据的实时性显著提升,且随着杂波数据量增大其加速效果更好,相较传统GPU方法计算速率提高61%。Modern radar clutter simulation needs to use clutter data for real-time analysis and processing of the echo signal.However,the traditional Spherically Invariant Random Process(SIRP)method for clutter data generation is time-consuming.By improving the SIRP method,this paper proposes a method to improve the real-time performance of clutter generation based on Graphic Processing Unit(GPU)parallel computing.In the Compute Unified Device Architecture(CUDA),the multi-task series-parallel analysis is carried out for the correlation coherent K-distribution clutter algorithm.In addition,the cuBLAS library is used to optimize the fine-grained convolution calculation,and the OpenMP+CUDA multi-task scheduling mechanism is used to improve the coarse-grained task parallel calculation in order to improve the CPU-GPU utilization and reduce the data waiting time.Experimental results show that compared with the traditional GPU method,the proposed method increases the calculation speed by 61%,and the real-time performance of clutter data generation is effectively improved.In addition,the acceleration effect significantly grows with the volume of clutter data.

关 键 词：雷达杂波 GPU并行计算 球不变随机过程法 卷积计算 cuBLAS库 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]