吉林大学学报(地球科学版) ›› 2017, Vol. 47 ›› Issue (4): 1308-1318.doi: 10.13278/j.cnki.jjuese.201704306

• 地球探测与信息技术 • 上一篇    下一篇

基于DOA估计的阵列式探地雷达逆向投影目标成像方法

曾昭发1, 李文奔1, 习建军1,2, 黄玲3, 王者江1   

  1. 1. 吉林大学地球探测科学与技术学院, 长春 130026;
    2. 河北省电力勘测设计研究院, 石家庄 050031;
    3. 中国科学院电子学研究所, 北京 100190
  • 收稿日期:2016-11-25 出版日期:2017-07-26 发布日期:2017-07-26
  • 通讯作者: 习建军(1982),男,博士研究生,工程师,主要从事工程物探及电力勘测工作,E-mail:tiantianhappy365@126.com E-mail:tiantianhappy365@126.com
  • 作者简介:曾昭发(1966),男,博士,教授,博士生导师,主要从事应用地球物理电磁法教学和研究工作,E-mail:zengzf@jlu.edu.cn
  • 基金资助:
    国家自然科学基金项目（40774055，41174097，41574097）；高等学校博士学科点专项科研基金项目（20130061110060）

Inverse Direction Imaging Method of Array Type GPR Based on DOA Estimation

Zeng Zhaofa1, Li Wenben1, Xi Jianjun1,2, Huang Ling3, Wang Zhejiang1   

  1. 1. College of GeoExploration Science and Technology, Jilin University, Changchun 130026, China;
    2. Hebei Electric Power Design ＆ Research Institute, Shijiazhuang 050031, China;
    3. Institute of Electronics, Chinese Academy of Sciences, Beijing 100190, China
  • Received:2016-11-25 Online:2017-07-26 Published:2017-07-26
  • Supported by:
    Supported by the National Natural Science Foundation of China (40774055, 41174097, 41574097) and the Specialized Research Fund for the Doctoral Program of Higher Education of China (20130061110060)

PDF (PC)

495

摘要： 本文针对阵列式天线探地雷达系统的目标成像问题，理论模拟分析了最小二乘（LS）估计、Capon估计、幅度相位估计（APES）三种波束形成算法在目标回波到达角（direction of arrival，DOA）估计上的效果和精度，提出了基于DOA估计的阵列式探地雷达逆向投影目标成像方法。该方法综合利用多输入多输出（MIMO）阵列信号估计得到的目标回波信号DOA和阵列空间观测信息对目标体进行成像，通过成像点空间扫描对各测点估计DOA幅度值在成像点的加权积分进行目标定位及反射强度估计。该方法实现简单高效，可以广泛应用于地下简单目标体的快速成像。

关键词: 最小二乘, Capon估计, 幅度相位估计, DOA估计, 目标成像, 探地雷达

Abstract: Taking the target imaging of array type ground penetrating radar system as the topic, the authors analyzed the effect and accuracy of the estimation for target echo arrival upon direction of arrival (DOA) in theoretical modeling with three beam forming algorithms, i.e., least square (LS), Capon algorithm and amplitude phase estimation (APES), and put forward a method of array type GPR target imaging based on DOA estimation. This method images the target by integrating the target echo arrival signal estimated from multiple-input-multiple-output(MIMO)array signals with the spatial information obtained from multiple array observations, and localizes target and estimates reflection intensity by the imaging points weighted integral based on the DOA amplitude value estimated from each point by way of imaging points spatial scanning. This method is simple and efficient, and can be used widely in the rapid imaging of simple underground targets.

Key words: least squares (LS), Capon algorithm, amplitude and phase estimation (APES), DOA estimation, target imaging, ground penetrating radar(GPR)

中图分类号: 

  • P631.3
[1] Jabbarian-Jahromi M, Kahaei M H. Two-Dimensional SLIM with Application to Pulse Doppler MIMO Radars[J]. Eurasip Journal on Advances in Signal Processing, 2015(1):1-12.
[2] 王天云. 分布式雷达稀疏成像技术研究[D]. 合肥:中国科学技术大学, 2015: 3-25. Wang Tianyun. Research on Distributed Radar Sparse Imaging Technologies [D]. Hefei: University of Science and Technology of China,2015: 3-25.
[3] 习建军,曾昭发,黄玲,等. 阵列式探地雷达信号极化场特征[J].吉林大学学报(地球科学版),2017,47(2):633-644. Xi Jianjun, Zeng Zhaofa, Huang Ling, et al. Characteristics of the Signal Polarization Field in Array Type Ground Penetrating Radar[J/OL]. Journal of Jilin University (Earth Science Edition), 2017, 47(2): 633-644.
[4] Tan X,Roberts W, Li J, et al. Sparse Learning via Iterative Minimization with Application to MIMO Radar Imaging[J]. Signal Processing, 2014, 59(3):1088-1101.
[5] Xu L Z,Li J,Stoica P. Radar Imaging via Adaptive MIMO Techniques[C]//The 14th European Signal Processing Conference. [S. l.]: IET, 2006:1-5.
[6] Tabrikian J. Barankin Bounds for Target Localization by MIMO Radars[C]//Sensor Array and Multichannel Processing. [S. l.]: IEEE, 2006:278-281.
[7] 王鞠庭,江胜利.复合高斯杂波中MIMO雷达DOA估计的克拉美-罗下限[J].电子与信息学报,2009,31(4):786-789. Wang Juting,Jiang Shengli. Cramer-Rao Bounds of DOA Estimation for MIMO Radars in Compound -Gaussian Clutter[J]. Journal of Electronics & Information Technology, 2009, 31(4): 786-789.
[8] 夏威,何子述.APES算法在MIMO雷达参数估计中的稳健性研究[J].电子学报,2008,36(9):1804-1809. Xia Wei, He Zishu. On the Robustness of the APES Algorithm in the Parameter Estimation of MIMO Radars[J]. Acta Electronica Sinica, 2008, 36(9): 1804-1809.
[9] 韩兴斌,胡卫东,郁文贤,等.分布式多通道雷达成像技术[J].电子与信息学报,2007,29(10):2354-2358. Han Xingbin,Hu Weidong,Yu Wenxian,et al. An Imaging Technique Based on Distributed Multi-Channel Radars[J]. Journal of Electronics & Information Technology, 2007, 29(10): 2354-2358.
[10] Li N, Cui G, Kong L, et al. MIMO RadarMoving Target Detection Against Compound-Gaussian Clutter[J]. Circuits Systems & Signal Processing, 2014, 33(6):1-21.
[11] Ma X Y,Wang D W,Su Y. High-Resolution Imaging Using a Narrowband MIMO Radar System[C]//The 9th Internation Conference on Signal Processing. Beijing: IET, 2008:2263-2267.
[12] Wang H J,Su Y. Narrowband MIMO Radar Imaging with Two Orthogonal Linear T/R arrays[C]//The 9th Internation Conference on Signal Processing. Beijing: IET, 2008:2513-2516.
[13] Zeng Zhaofa, Li Jing,Huang Ling,et al. Improving Target Detection Accuracy Based on Multipolarization MIMO GPR[J]. Geosciences and Remote Sensing, 2015, 53(1): 15-24.
[14] Zhao Y N, Li F C, Zhang T, et al.Computational Design of Optimal Waveforms for MIMO Radar via Multi-Dimensional Iterative Spectral Approximation[J]. Multidimensional Systems & Signal Processing, 2016: 27(1): 1-18.
[15] Fuhnrmann D R, Antonio G S. Transmit Beamfo-nning for MIMO Radar Systems Using Partial Signal Correlation[C]//Conference Record of The 38th Asilmar Conference on Signals Systems and Computers. [S. l.]: IET, 2014:295-299.
[16] Liu X, Sun C, Zhuo J, et al. High-Resolution Swath Bathymetry Using MIMO Sonar System [J]. Journal of Systems Engineering and Electronics, 2014, 25(5): 761-768.
[1] 梁文婧, 冯晅, 刘财, 恩和得力海, 张明贺, 梁帅帅. 多输入多输出极化步进频率探地雷达硬件系统开发[J]. 吉林大学学报(地球科学版), 2018, 48(2): 483-490.
[2] 孙建国, 李懿龙, 孙章庆, 苗贺. 基于模型参数化的地震波走时与射线路径计算[J]. 吉林大学学报(地球科学版), 2018, 48(2): 343-349.
[3] 冯晅, 梁帅帅, 恩和得力海, 张明贺, 董泽君, 周皓秋, 齐嘉慧, 赵玮昌. 全极化探地雷达地下管道分类识别技术[J]. 吉林大学学报(地球科学版), 2018, 48(2): 364-372.
[4] 王文天, 刘四新, 鹿琪, 李宏卿, 傅磊. 基于改进残差法的定向钻孔雷达三维成像算法[J]. 吉林大学学报(地球科学版), 2018, 48(2): 402-410.
[5] 王宪楠, 刘四新, 程浩. Shearlet变换在GPR数据随机噪声压制中的应用[J]. 吉林大学学报(地球科学版), 2017, 47(6): 1855-1864.
[6] 习建军, 曾昭发, 黄玲, 崔丹丹, 王者江. 阵列式探地雷达信号极化场特征[J]. 吉林大学学报(地球科学版), 2017, 47(2): 633-644.
[7] 孟庆生, 韩凯, 刘涛, 高镇. 软土基坑隔水帷幕渗漏检测技术[J]. 吉林大学学报(地球科学版), 2016, 46(1): 295-302.
[8] 牟丹, 王祝文, 黄玉龙, 许石, 周大鹏. 基于最小二乘支持向量机测井识别火山岩类型:以辽河盆地中基性火山岩为例[J]. 吉林大学学报(地球科学版), 2015, 45(2): 639-648.
[9] 李伟东，林楠，刘德利，孙晓磊. 用于变形监测的最小二乘滤波数据处理[J]. 吉林大学学报(地球科学版), 2014, 44(6): 2068-2072.
[10] 黄修东，束龙仓，崔峻岭，童坤,周庆鹏. 人工回灌物理堵塞特征试验及渗滤经验公式推导[J]. 吉林大学学报(地球科学版), 2014, 44(6): 1966-1972.
[11] 黄建平，薛志广，步长城，李振春，王常波，高国超，曹晓莉，李国磊. 基于裂步DSR的最小二乘偏移方法[J]. 吉林大学学报(地球科学版), 2014, 44(1): 369-374.
[12] 张丽丽, 刘四新, 吴俊军, 贾亮, 康晓涛. 基于分数阶傅里叶变换的探地雷达子波提取算法[J]. J4, 2012, 42(2): 569-574.
[13] 佴磊, 彭文, 袁明哲, 周能娟. 基于经验模态分解和加权最小二乘支持向量机的采空区地面塌陷预测[J]. J4, 2011, 41(3): 799-804.
[14] 陈永良, 李学斌. 基于核最小二乘模型的矿产靶区预测[J]. J4, 2011, 41(3): 937-944.
[15] 温忠辉, 任化准, 束龙仓, 王恩, 柯婷婷, 陈荣波. 岩溶地下河日流量预测的小样本非线性时间序列模型[J]. J4, 2011, 41(2): 455-458.
Viewed
Full text


Abstract

Cited
  Shared   
  Discussed   
No Suggested Reading articles found!
版权所有 © 《吉林大学学报(地球科学版)》编辑部
地址：长春市西民主大街938号(130026)　电话：+86-431-88502374；13756165364　E-mail: xuebao1956@jlu.edu.cn
本系统由北京玛格泰克科技发展有限公司设计开发