基于十字型阵列的并行子阵波束形成算法

doi:10.13229/j.cnki.jdxbgxb201604045

吉林大学学报(工学版) ›› 2016, Vol. 46 ›› Issue (4): 1330-1336.doi: 10.13229/j.cnki.jdxbgxb201604045

基于十字型阵列的并行子阵波束形成算法

刘雪松^{1, 2}, 周凡^{1, 2, 3}, 周泓^{1, 2}, 田翔^{1, 2, 3}, 蒋荣欣^{1, 2, 3}, 陈耀武^{1, 2, 3}

1.浙江大学数字技术及仪器研究所,杭州 310027;
2.浙江省网络多媒体技术研究重点实验室,杭州 310027;
3.浙江大学工业控制技术国家重点实验室,杭州 310027

收稿日期:2015-01-28 出版日期:2016-07-20 发布日期:2016-07-20
通讯作者: 周凡(1978-),男,副教授,博士.研究方向:嵌入式系统,声纳信号处理,多媒体技术,FPGA并行计算.E-mail:fanzhou@mail.bme.zju.edu.cn
作者简介:刘雪松(1988-),男,博士研究生.研究方向:嵌入式系统,声纳信号处理.E-mail:11015006@zju.edu.cn
基金资助:
国家自然科学基金项目(41276090); “863”国家高技术研究发展计划项目(2014AA091301); 中央高校基本科研业务费专项资金项目

Parallel subarray beamforming algorithm based on cross array

LIU Xue-song^{1, 2}, ZHOU Fan^{1, 2, 3}, ZHOU Hong^{1, 2}, TIAN Xiang^{1, 2, 3}, JIANG Rong-xin^{1, 2, 3}, CHEN Yao-wu^{1, 2, 3}

1.Institute of Advanced Digital Technology and Instrumentation, Zhejiang University,Hangzhou 310027,China;
2.Zhejiang Provincial Key Laboratory for Network Multimedia Technologies,Hangzhou 310027,China;
3.State Key Laboratory of Industrial Control Technology,Zhejiang University,Hangzhou 310027,China

Received:2015-01-28 Online:2016-07-20 Published:2016-07-20

摘要/Abstract

摘要： 针对基于平面阵三维声纳成像系统应用中硬件开销及波束形成计算量大的问题,提出了一种基于十字型阵列的并行子阵波束形成算法。十字型阵列采用两条一维线阵实现了三维声纳成像,相比于二维平面阵,极大地简化了硬件复杂度。并行子阵算法在此基础上对十字型阵列的接收波束形成过程进行优化。算法将接收阵划分为多个子阵,在各子阵上并行地进行一级频域波束形成,在各子阵之间执行二级波束域波束形成,该两级并行流水线结构,有效地降低了波束形成的计算量。此外,给出了算法在现场可编程门阵列(FPGA)平台上的实现架构。仿真结果显示:本文算法获得了与直接波束形成相近的波束性能,但计算量仅为其一半,并且随着波束数量的增加,其优势会更加明显。

关键词: 信息处理技术, 并行子阵波束形成, 子阵划分, 十字型阵列, 计算量需求

Abstract: To overcome the problem of huge hardware cost and computational load associated with the planar array in 3D sonar imaging application, a parallel subarray beamforming algorithm based on the cross array is proposed. The cross array can achieve 3D sonar image by two 1D linear arrays, which greatly simplifies the hardware complexity compared to planar array. The proposed algorithm is applied to optimize the receiving beamforming procedure of the cross array, and subdivide the receiving array into several subarrays. The first-stage frequency-domain beamforming is performed simultaneously in each subarray, and the second-stage beam-domain beamforming is implemented between the subarrays. The two-stage parallel and pipeline framework efficiently reduces the computational requirement of the beamforming. Moreover, the architecture of the algorithm on Field Programmable Gate Array (FPGA) is given. The simulation and analysis results demonstrate that the proposed algorithm can achieve similar beam performance but save half of the computational requirement compared to the direct method. As the number of beams increases, the superiority of the proposed algorithm becomes more obvious.

Key words: information processing, parallel subarray beamforming, subarray decomposition, cross array, computational requirement

中图分类号:

TN911.7

刘雪松, 周凡, 周泓, 田翔, 蒋荣欣, 陈耀武. 基于十字型阵列的并行子阵波束形成算法[J]. 吉林大学学报(工学版), 2016, 46(4): 1330-1336.

LIU Xue-song, ZHOU Fan, ZHOU Hong, TIAN Xiang, JIANG Rong-xin, CHEN Yao-wu. Parallel subarray beamforming algorithm based on cross array[J]. 吉林大学学报(工学版), 2016, 46(4): 1330-1336.

参考文献

[1] Murino V, Trucco A. Three-dimensional image generation and processing in underwater acoustic vision[J]. Proceedings of the IEEE, 2000, 88(12): 1903-1948.
[2] Wachowski N, Azimi-Sadjadi M R. A new synthetic aperture sonar processing method using coherence analysis[J]. IEEE Journal of Oceanic Engineering, 2011, 36(4): 665-678.
[3] Palmese M, Trucco A. Acoustic imaging of underwater embedded objects: signal simulation for three-dimensional sonar instrumentation[J]. IEEE Transactions on Instrumentation and Measurement, 2006, 55(4): 1339-1347.
[4] Nielsen R O. Sonar Signal Processing[M]. Boston: Artech House, 1991: 51-52.
[5] Trucco A. Thinning and weighting of large planar arrays by simulated annealing[J]. IEEE Transactions on Ultrasonics, Ferroelectrics and Frequency Control, 1999, 46(2): 347-355.
[6] Repetto S, Palmese M, Trucco A. Design and assessment of a low-cost 3-D sonar imaging system based on a sparse array[C]∥IEEE Instrumentation and Measurement Technology Conference, Sorrento,2006: 410-415.
[7] 陈朋,陈耀武. 三维声纳频域波束形成算法的优化及实现[J]. 吉林大学学报:工学版, 2010,40(3):830-835.
Chen Peng, Chen Yao-wu. 3D sonar frequency-domain beamforming algorithm-optimization and implementation[J]. Journal of Jilin University (Engineering and Technology Edition), 2010,40(3):830-835.
[8] Palmese M, Trucco A. Three-Dimensional acoustic imaging by chirp zeta transform digital beamforming[J]. IEEE Transactions on Instrumentation and Measurement, 2009, 58(7): 2080-2086.
[9] MacPhie R H. A mills cross multiplicative array with the power pattern of a conventional planar array[C]∥Proc IEEE Antennas and Propagation Soc Int Symp, Honolulu,HI,2007: 5961-5964.
[10] Henderson T L,Lacker S G.Seafloor profiling by a wideband sonar:simulation,frquency-response optimization,and results of a brief sea test[J].IEEE Journal of Oceanic Engineering,1989,14(1):94-107.
[11] Okino M, Higashi Y. Measurement of seabed topography by multibeam sonar using CFFT[J]. IEEE Journal of Oceanic Engineering, 1986, 11(4): 474-479.
[12] Volder J E. The CORDIC trigonometric computing technique[J]. IRE Trans on Electronic Computers, 1959,8(3): 330-334.

相关文章 15

[1]	苏寒松,代志涛,刘高华,张倩芳. 结合吸收Markov链和流行排序的显著性区域检测[J]. 吉林大学学报(工学版), 2018, 48(6): 1887-1894.
[2]	徐岩,孙美双. 基于卷积神经网络的水下图像增强方法[J]. 吉林大学学报(工学版), 2018, 48(6): 1895-1903.
[3]	黄勇,杨德运,乔赛,慕振国. 高分辨合成孔径雷达图像的耦合传统恒虚警目标检测[J]. 吉林大学学报(工学版), 2018, 48(6): 1904-1909.
[4]	李居朋,张祖成,李墨羽,缪德芳. 基于Kalman滤波的电容屏触控轨迹平滑算法[J]. 吉林大学学报(工学版), 2018, 48(6): 1910-1916.
[5]	应欢,刘松华,唐博文,韩丽芳,周亮. 基于自适应释放策略的低开销确定性重放方法[J]. 吉林大学学报(工学版), 2018, 48(6): 1917-1924.
[6]	陆智俊,钟超,吴敬玉. 星载合成孔径雷达图像小特征的准确分割方法[J]. 吉林大学学报(工学版), 2018, 48(6): 1925-1930.
[7]	刘仲民,王阳,李战明,胡文瑾. 基于简单线性迭代聚类和快速最近邻区域合并的图像分割算法[J]. 吉林大学学报(工学版), 2018, 48(6): 1931-1937.
[8]	单泽彪,刘小松,史红伟,王春阳,石要武. 动态压缩感知波达方向跟踪算法[J]. 吉林大学学报(工学版), 2018, 48(6): 1938-1944.
[9]	姚海洋, 王海燕, 张之琛, 申晓红. 双Duffing振子逆向联合信号检测模型[J]. 吉林大学学报(工学版), 2018, 48(4): 1282-1290.
[10]	全薇, 郝晓明, 孙雅东, 柏葆华, 王禹亭. 基于实际眼结构的个性化投影式头盔物镜研制[J]. 吉林大学学报(工学版), 2018, 48(4): 1291-1297.
[11]	陈绵书, 苏越, 桑爱军, 李培鹏. 基于空间矢量模型的图像分类方法[J]. 吉林大学学报(工学版), 2018, 48(3): 943-951.
[12]	陈涛, 崔岳寒, 郭立民. 适用于单快拍的多重信号分类改进算法[J]. 吉林大学学报(工学版), 2018, 48(3): 952-956.
[13]	孟广伟, 李荣佳, 王欣, 周立明, 顾帅. 压电双材料界面裂纹的强度因子分析[J]. 吉林大学学报(工学版), 2018, 48(2): 500-506.
[14]	林金花, 王延杰, 孙宏海. 改进的自适应特征细分方法及其对Catmull-Clark曲面的实时绘制[J]. 吉林大学学报(工学版), 2018, 48(2): 625-632.
[15]	王柯, 刘富, 康冰, 霍彤彤, 周求湛. 基于沙蝎定位猎物的仿生震源定位方法[J]. 吉林大学学报(工学版), 2018, 48(2): 633-639.

Metrics

Viewed

Full text

Abstract

Cited

Shared

Discussed

基于十字型阵列的并行子阵波束形成算法

Parallel subarray beamforming algorithm based on cross array

RICH HTML

PDF (PC)

摘要/Abstract

引用本文

使用本文

参考文献

相关文章 15

Metrics

本文评价

推荐阅读 10