Current Science

Open Access Open Access  Restricted Access Subscription Access

A Target Imaging Method of Multiple-Input-Multiple-Output Ground Penetrating Radar-Based on Direction of Arrival Estimation


Affiliations
1 Powerchina Hebei Electric Power Design & Research Institute Co. LTD, Shijiazhuang 050031, China
2 Institute of Electronics, Chinese Academy of Sciences, Beijing 100190, China
 

In this study we consider imaging of the multiple-input-multiple-output ground penetrating radar (MIMO-GPR) system, and analyse the effect and accuracy of the estimation for target echo arrival upon direction of arrival (DOA) in the three beam-forming algorithms, i.e. least square, Capon algorithm and amplitude phase estimation. We propose a method of multi-antenna GPR target imaging based on the DOA estimation. This method, to perform the target imaging, makes combined use of DOA estimation of target echo signal in MIMO array and array spatial observation information. By spatial scanning for the imaging points, the target is localized and the reflection intensity is estimated from the weighted integral of each estimated DOA amplitude value at the imaging point. This method, with simpler practice, less data observation frequency and more efficient calculation, can speed up the target detection measurement and improve the data interpretation efficiency.

Keywords

Beam-Forming Algorithms, Direction of Arrival Estimation, Ground Penetrating Radar, Target Imaging.
User
Notifications
Font Size

  • Roberts, W. et al., Sparse learning via iterative minimization with application to MIMO radar imaging. IEEE Trans. Signal Proc., 2014, 59(3), 1088–1101.

  • Xu, L. Z., Li, J. and Stoica, P., Radar imaging via adaptive MIMO techniques. In 14th European Signal Processing Conference, Florence, 2006, pp. 1–5.

  • Tabrikian, J., Barankin bounds for target localization by MIMO radars. In Fourth IEEE Workshop on Sensor Array and Multi-channel Processing, 2006, pp. 278–281.

  • Ju-Ting, W. and Shengli, J., Cramer-Rao bounds of DOA estimation for MIMO radars in compound-Gaussian clutter. J. Electron. Infor. Technol., 2009, 31(4), 786–789.

  • Wei, X. and Zi-Zhu, H., On the robustness of the APES algorithm in the parameter estimation of MIMO radars. Acta Electron. Sin., 2008, 36(9), 1804–1809.

  • Xing-Bin, H. et al., An Imaging technique based on distributed multi-channel radars. J. Electron. Infor. Technol., 2007, 29(10), 2354–2358.

  • Ma, X. Y., Wang, D. W. and Su, Y., High-resolution imaging using a narrowband MIMO radar system. In The 9th International Conference on Signal Processing, Beijing, China, 2008, pp. 2263–2267.

  • Wang, H. J. and Su, Y., Narrowband MIMO radar imaging with two orthogonal linear T/R arrays. In The 9th International Conference on Signal Processing, Beijing, China, 2008, pp. 2513–2516.

  • Ji-Yu, S., Electromagnetic analysis and simulation of MIMO radar imaging. Ph D thesis, Harbin University of Science and Technology, Harbin, China, 2012, pp. 23–33.

  • Jabbarian-Jahromi, M. and Kahaei, M. H., Two-dimensional SLIM with application to pulse Doppler MIMO radars. Eur. J. Adv. Signal. Process., 2015, 2015, 1–12.

  • Tian-Yun, W., Research on distributed radar sparse imaging technologies, Ph D thesis, University of Science and Technology of China, China, 2015, pp. 3–25.

  • Zeng, Z. et al., Improving target detection accuracy based on multipolarization MIMO GPR. IEEE Trans. Geosci. Remote Sensing, 2015, 53(1), 15–24.

  • Zhao, Y. N. et al., Computational design of optimal waveforms for MIMO radar via multi-dimensional iterative spectral approximation. Multidimen. Syst. Signal. Process., 2014, 27(1), 1–18.

  • Li, L. and Tian-Shuang, Q., Novel method for joint parameter estimation based on FPSD in wideband bistatic MIMO radar system. J. Commun., 2014, 35(6), 192–199.

  • Li, N. et al., MIMO radar moving target detection against compound-Gaussian clutter. Circuits Syst. Signal Process., 2014, 33(6), 1–21.

  • Liu, X. et al., High-resolution swath bathymetry using MIMO sonar system. J. Syst. Eng. Electron., 2014, 25(5), 761–768.

  • Wei, X., MIMO radar model and the signal processing research. Ph D thesis, Xidian University, Xi’an, 2007, pp. 3–8.

  • Li, J., MIMO Radar Signal Processing, John Wiley, New Jersey, USA, 2009, pp. 2–60.

  • Nehorai, A., Starer, D. and Stoica, P., Direction-of-arrival estimation in applications with multipath and few snapshots. Circuits, Syst. Signal. Process., 1991, 10(3), 327–342.

  • Bo, L., Orthogonal waveform MIMO radar signal design and processing. Ph D thesis, University of Electronic Science and Technology, Chengdu, 2008, pp. 9–30.

  • Fuhnrmann, D. R. and Antonio, G. S., Transmit beamfonning for MIMO radar systems using partial signal correlation. In 38th Asilmar Conference on Signals Systems and Computers, 2014, vol. 1, pp. 295–299.

  • Donnet, B. J. and Longstaff, I. D., Combining MIMO radar with OFDM Comunications. In 3rd European Radar Conference, 2006, vol. 1, pp. 37–40.


Abstract Views: 465

PDF Views: 152




  • A Target Imaging Method of Multiple-Input-Multiple-Output Ground Penetrating Radar-Based on Direction of Arrival Estimation

Abstract Views: 465  |  PDF Views: 152

Authors

Xi Jianjun
Powerchina Hebei Electric Power Design & Research Institute Co. LTD, Shijiazhuang 050031, China
Huang Ling
Institute of Electronics, Chinese Academy of Sciences, Beijing 100190, China

Abstract


In this study we consider imaging of the multiple-input-multiple-output ground penetrating radar (MIMO-GPR) system, and analyse the effect and accuracy of the estimation for target echo arrival upon direction of arrival (DOA) in the three beam-forming algorithms, i.e. least square, Capon algorithm and amplitude phase estimation. We propose a method of multi-antenna GPR target imaging based on the DOA estimation. This method, to perform the target imaging, makes combined use of DOA estimation of target echo signal in MIMO array and array spatial observation information. By spatial scanning for the imaging points, the target is localized and the reflection intensity is estimated from the weighted integral of each estimated DOA amplitude value at the imaging point. This method, with simpler practice, less data observation frequency and more efficient calculation, can speed up the target detection measurement and improve the data interpretation efficiency.

Keywords


Beam-Forming Algorithms, Direction of Arrival Estimation, Ground Penetrating Radar, Target Imaging.

References





DOI: https://doi.org/10.18520/cs%2Fv114%2Fi05%2F1014-1023