期刊文献+

基于时分MIMO的地基雷达高分辨率成像研究 被引量:2

Study on High-resolution Imaging of Ground-based MIMO Radar Based on Time-division Multiplexing
在线阅读 下载PDF
导出
摘要 基于时分多输入多输出(MIMO)的地基雷达成像有许多很好的应用价值,比如替代合成孔径雷达成像在山体滑坡监测方面的应用。针对基于时分MIMO的地基雷达高效高分辨率成像,该文提出一种基于逆傅里叶变换脉冲压缩和波束形成的成像算法。雷达通过步进频连续波技术获得高距离向分辨率,利用MIMO技术获得高方位向分辨率。通过逆傅里叶变换法实现雷达数据距离向压缩,采用波束形成算法实现雷达数据方位向压缩。同时该算法还针对MIMO天线阵列所引起的回波信号相位不连续问题进行了适当的校正,在保持算法高效性的同时提高了成像质量。根据真实的山体滑坡监测成像场景参数,通过数值仿真验证了该成像算法的可行性,应用在山体滑坡监测上理论效果良好。 Ground-based radar imaging based on time-division multiplexing MIMO can be used in many important applications, such as application to landslide monitoring in place of synthetic aperture radar imaging. For efficient high-resolution imaging of the ground-based radar based on time-division multiplexing MIMO, an imaging algorithm based on Inverse Fast Fourier Transform(IFFT) pulse compression and beamforming is proposed. High range resolution is obtained by stepped frequency continuous wave technology and high azimuth resolution is obtained by MIMO technology. The range compression of radar data is realized by IFFT and the cross-range compression of radar data is realized by beamforming algorithm. Furthermore, phase discontinuity problem of received signal caused by MIMO antenna arrays is appropriately corrected in the algorithm, both efficiency of this algorithm and imaging quality are also improved. A numerical simulation proves feasibility of this imaging algorithm according to the practical parameters in monitoring and imaging scenario of landslide, and the proposed imaging algorithm has good theoretical performance when it is applied to landslide monitoring.
出处 《电子与信息学报》 EI CSCD 北大核心 2016年第5期1055-1063,共9页 Journal of Electronics & Information Technology
基金 国家自然科学基金(61561010) 广西自然科学基金项目(2013GXNSFAA019323) 广西科学研究与技术开发计划项目(桂科攻14122006-6) 广西教育厅科研立项项目(KY2015LX096) 广西无线宽带通信与信号处理重点实验室主任基金项目(GXKL061506)
关键词 雷达成像 时分MIMO雷达 高分辨率 波束形成 逆傅里叶变换脉冲压缩 Radar imaging Time-division multiplexing MIMO radar High-resolution Beamforming Inverse Fast Fourier Transform(IFFT) pulse compression
作者简介 通信作者:蒋留兵jlbnj@163.com,蒋留兵:男,1973年生,研究员,主要研究方向为雷达信号处理、智能信号处理. 杨涛:男,1989年生,硕士,主要研究方向为MIMO雷达成像技术及其在微小形变探测方面的应用. 车俐:女,1977年生,高级实验师,主要研究方向为雷达信号处理.
  • 相关文献

参考文献16

  • 1MONSERRAT O, CROSETTO M, and LUZI G. A review of ground-based SAR interferometry for deformation measurement[J]. ISPRS Journal of Photogrammetry and Remote Sensing, 2014, 93: 40-48. doi: 10.1016/j.isprsjprs. 2014.04.001.
  • 2LEVA D, NICO G, TARCHI D, et al. Temporal analysis of a landslide by means of a ground-based SAR interferometer[J]. IEEE Transactions on Geoscience and Remote Sensing, 2003, 41(4): 745-752. doi: 10.1109/TGRS.2003.808902.
  • 3HAKOBYAN A, MCGUIRE P, POWER D, et al. Applications and validation tests of ground-based coherent radar for deformation and vibration measurements in Canada's Atlantic region[C]. 2015 IEEE 28th Canadian Conference on Electrical and Computer Engineering (CCECE), Halifax, NS, 2015: 638-642. doi: 10.1109/CCECE. 2015.7129349.
  • 4LUO Y, SONG H, WANG R, et al. Arc FMCW SAR and applications in ground monitoring[J]. IEEE Transactions on Geoscience and Remote Sensing, 2014, 52(9): 5989-5998. doi: 10.1109/TGRS.2014.2325905.
  • 5MAO C, LIU F, NI C, et al. GB-SAR deformation monitoring: Performance analysis and primary experimental results[C]. IET International Radar Conference 2013, Xi’an, 2013: 1-6. doi: 10.1049/cp.2013.0192.
  • 6TARCHI D, OLIVERI F, and SAMMARTINO P F. MIMO radar and ground-based SAR imaging systems: equivalent approaches for remote sensing[J]. IEEE Transactions on Geoscience and Remote Sensing, 2013, 51(1): 425-435. doi:10.1109/TGRS.2012.2199120.
  • 7王怀军,黄春琳,陆珉,粟毅.MIMO雷达反向投影成像算法[J].系统工程与电子技术,2010,32(8):1567-1573. 被引量:20
  • 8王伟,马跃华,王咸鹏.一种高运算效率的MIMO雷达BP成像算法[J].系统工程与电子技术,2013,35(10):2080-2085. 被引量:8
  • 9KLARE J and SAALMANN O. MIRA-CLE X: a new imaging MIMO-radar for multi-purpose applications[C]. 2010 European Radar Conference (EuRAD), Paris, 2010: 129-132.
  • 10SAMMARTINO P F, TARCHI D, and BAKER C J. MIMO radar topology: A systematic approach to the placement of the antennas[C]. 2011 International Conference on Electromagnetics in Advanced Applications (ICEAA), Torino, 2011: 114-117. doi: 10.1109/ICEAA.2011.6046337.

二级参考文献63

  • 1CUMMINGIG,WONGFH.合成孔径雷达成像-算法与实现[M].洪文,胡东辉译.北京:电子工业出版社,2007:219-248.
  • 2Bliss D W,Forsythe K W.Multiple-input multiple-output (MIMO) radar and imaging:degrees of freedom and resolution[C]//Proc.of the 37th Asilomar Conference on Signals,Systems and Computers,Pacific Grove,CA:IEEE Press,2003:54-59.
  • 3Rabideau D J,Parker P.Ubiquitous MIMO multifunction digital array radar[C]// Proc.of the 37th Asilomar Conference on Signals,Systems and Computers,Pacific Grove,CA:IEEE Press,2003:1057-1064.
  • 4Fishler E,Haimovich A,Blum R,et al.MIMO radar:an idea whose time has come[C]// Proc.of IEEE Radar Conference,Philadelphia,PA:IEEE Press,2004:71-78.
  • 5Fishler E,Haimovich A,Blum R,et al.Performance of MIMO radar systems:advantages of angular diversity[C]// Proc.of the 38th Conference on Signals System and Computers,Pacific Grove,CA:IEEE Press,2004:7-10.
  • 6Forsythe K W,Bliss D W,Fawcett G S.Multiple-input multiple-output (MIMO) radar:performance issues[C]// Proc.of the 38th Conference on Signals System and Computers,Pacific Grove,CA:IEEE Press,2004:310-315.
  • 7Robey F C,Coutts S,Weikle D,et al.MIMO radar theory and experimental results[C]// Proc.of the 38th Conference on Signals System and Computers,Pacific Grove,CA:IEEE Press,2004:300-304.
  • 8Li J,Stoica P,Zheng X.Signal synthesis and receiver design for MIMO radar imaging[J].IEEE Trans.on Signal Processing,2008,56(8):3959-3968.
  • 9McCorkle J W.Focusing of synthetic aperture ultra wideband data[C]// Proc.of IEEE International Conference on System Engineering,Dayton,OH:IEEE Press,1991:1-5.
  • 10Fletcher A S,Robey F C.Performance bounds for adaptive coherence of sparse array radar[C]// Proc.of the 11th Conference on Adaptive Sensors Array Processing,Lexington,MA:MIT Lincoln Laboratory,2003:1-6.

共引文献54

同被引文献8

引证文献2

二级引证文献3

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部