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An Entropy-Based MIMO Array Optimization for Short-Range UWB Imaging

Received: 4 May 2016     Published: 9 May 2016
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Abstract

A novel approach to design the position of linear Multiple-Input Multiple-Output (MIMO) array elements for short-range UWB imaging is proposed. The proposed method uses Particle Swarm Optimization (PSO) algorithm to determine the optimal MIMO antenna array topologies that can provide minimum entropy of the reconstructed image. According to the approach, a MIMO array is optimized with minimum entropy indicating high focusing quality.

Published in International Journal of Wireless Communications and Mobile Computing (Volume 4, Issue 2)
DOI 10.11648/j.wcmc.20160402.14
Page(s) 32-36
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2016. Published by Science Publishing Group

Keywords

Array Design, UWB, MIMO, Entropy, PSO

References
[1] Edward J. Baranoski. Through-wall imaging Historical perspective and future directions [J]. Journal of the Franklin Institute. 2008, 345: 556-569.
[2] Stanley E. Borek. An Overview of Through the Wall Surveillance for Homeland Security [J]. Applied Imagery and Pattern Recognition Workshop, 2005.
[3] Laila Sakkila, Charles Tatkeu, Yassin El Hillali. UWB short range radar for road applications [J]. Physical and Chemical News, 2012, 64, p20-29.
[4] Zhuge Xiaodong. Short-range ultra-wideband imaging with multi-input multi-output arrays [D], Delft University of technology, 2010.
[5] A. Martinez-Vazquez, UWB MIMO Radar Arrays for Small Area Surveillance Applications [C], Proc. of 2nd EuCAP, 2007.
[6] L. Frazier, MDR for Law Enforcement [J], IEEE Potentials, Vol. 16, No. 5, pp. 23-26, 1998.
[7] Genyuan Wang, Imaging Through Unknown Walls Using Different Standoff Distances [J], IEEE Transactions on Signal Prossing, Vol 54, No. 10, Oct 2006, pp. 4015-4025.
[8] Francesco Soldovieri, A Multiarray Tomographic Approach for Through-Wall Imaging [J], IEEE Transactions on Geoscience and Remote Sensing, Vol, 46, No. 4, April 2008, pp. 1192-1199.
[9] Allan R. Hunt. Image Formation Through Walls Using a Distributed Radar Sensor Array [C]. Applied Imagery and Pattern Recognition Workshop, 2003.
[10] Calvin Le, Traian Dogaru, Lam Nguyen, Marc A. Ressler. Ultra-wideband (UWB) Radar Imaging of Building interior: Measurements and Predictions [C]. IEEE Transactions on Geoscience and Remote Sensing, 2009, vol. 47. 1409-1420.
[11] B. Yang, UWB MIMO Antenna Array Topology Design Using PSO for Through Dress Near-field Imaging [C], EuMA, Oct 2008, pp. 1620-1623.
[12] A. G. Yarovoy. Comparison of UWB Technologies for Human Being Detection with Radar [C], Proc. of 4th EuRAD, 2007, pp. 295-298.
[13] J. L. Schwartz, Ultrasparse, Ultrawideband Arrays, IEEE Trans. on Ultrasonics, Ferroelectrics, and Frequency Control [J], Vol. 45, No. 2, March 1998, pp. 376-393.
[14] M. Ciattaglia, Time Domain Synthesis of UWB Arrays [C], Proc. of 2nd EuCAP, 2007.
[15] Zhi Li, Tian Jin, Bo Chen, Zhimin Zhou. A coarray based MIMO array design method for UWB imaging [C]. IET International Radar Conference 2012, Glasgow, UK, 2012.
[16] Fauzia Ahmad, Saleem A. Kassam. Coarray analysis of the wide-band point spread function for active array imaging [J]. Signal Processing, Vol. 81, pp. 99-115, 2001.
[17] Cui G, Kong L, Yang J. A Back-Projection Algorithm to Stepped-Frequency Synthetic Aperture Through-the-Wall Radar Imaging [C]. Synthetic Aperture Radar, 2007. Apsar 2007. Asian and Pacific Conference on. 2007: 123 - 126.
[18] Chen A L, Wang D W, Ma X Y. An improved BP algorithm for high-resolution MIMO imaging radar [C].Audio Language and Image Processing (ICALIP), 2010 International Conference on. 2010:1663 - 1667.
[19] Ahmad F, Kassam S A. Coarray analysis of the wide-band point spread function for active array imaging [J]. Signal Processing, 2001, 81(1): 99-115.
[20] Dian Palupi Rini, Particle Swarm Optimization: Technique, System and Challenges [J]. International Journal of Computer Applications, vol. 14, No.1, January 2011.
[21] M. B. Ghalia, Particle Swarm Optimization with an Improved Exploration-Exploitation Balance [J], IEEE, vol. 3, 2008.
[22] J. Sok-Son,G. Thomas, Range-Doppler Radar Imaging and Motion Compensation [J], Artech House, Norwood, Mass, USA, 2001.
[23] Daniel Flores-Tapia, An Entropy-Based Propagation Speed Estimation Method for Near-Field Subsurface Radar Imaging [J], EURASIP Journal, 2010.
[24] Pun T. A New Method for Grey-Level Picture Thresholding Using the Entropy of the Histogram [J]. Signal Processing, 1980, 2(3): 223-237.
[25] Qu L, Yang T. Investigation of Air/Ground Reflection and Antenna Beamwidth for Compressive Sensing SFCW GPR Migration Imaging [J]. IEEE Transactions on Geoscience & Remote Sensing, 2012, 50(8): 3143-3149.
Cite This Article
  • APA Style

    Li Zhi, Zhang Jianwen, Shen Yu, Hu Jun. (2016). An Entropy-Based MIMO Array Optimization for Short-Range UWB Imaging. International Journal of Wireless Communications and Mobile Computing, 4(2), 32-36. https://doi.org/10.11648/j.wcmc.20160402.14

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    ACS Style

    Li Zhi; Zhang Jianwen; Shen Yu; Hu Jun. An Entropy-Based MIMO Array Optimization for Short-Range UWB Imaging. Int. J. Wirel. Commun. Mobile Comput. 2016, 4(2), 32-36. doi: 10.11648/j.wcmc.20160402.14

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    AMA Style

    Li Zhi, Zhang Jianwen, Shen Yu, Hu Jun. An Entropy-Based MIMO Array Optimization for Short-Range UWB Imaging. Int J Wirel Commun Mobile Comput. 2016;4(2):32-36. doi: 10.11648/j.wcmc.20160402.14

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  • @article{10.11648/j.wcmc.20160402.14,
      author = {Li Zhi and Zhang Jianwen and Shen Yu and Hu Jun},
      title = {An Entropy-Based MIMO Array Optimization for Short-Range UWB Imaging},
      journal = {International Journal of Wireless Communications and Mobile Computing},
      volume = {4},
      number = {2},
      pages = {32-36},
      doi = {10.11648/j.wcmc.20160402.14},
      url = {https://doi.org/10.11648/j.wcmc.20160402.14},
      eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.wcmc.20160402.14},
      abstract = {A novel approach to design the position of linear Multiple-Input Multiple-Output (MIMO) array elements for short-range UWB imaging is proposed. The proposed method uses Particle Swarm Optimization (PSO) algorithm to determine the optimal MIMO antenna array topologies that can provide minimum entropy of the reconstructed image. According to the approach, a MIMO array is optimized with minimum entropy indicating high focusing quality.},
     year = {2016}
    }
    

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  • TY  - JOUR
    T1  - An Entropy-Based MIMO Array Optimization for Short-Range UWB Imaging
    AU  - Li Zhi
    AU  - Zhang Jianwen
    AU  - Shen Yu
    AU  - Hu Jun
    Y1  - 2016/05/09
    PY  - 2016
    N1  - https://doi.org/10.11648/j.wcmc.20160402.14
    DO  - 10.11648/j.wcmc.20160402.14
    T2  - International Journal of Wireless Communications and Mobile Computing
    JF  - International Journal of Wireless Communications and Mobile Computing
    JO  - International Journal of Wireless Communications and Mobile Computing
    SP  - 32
    EP  - 36
    PB  - Science Publishing Group
    SN  - 2330-1015
    UR  - https://doi.org/10.11648/j.wcmc.20160402.14
    AB  - A novel approach to design the position of linear Multiple-Input Multiple-Output (MIMO) array elements for short-range UWB imaging is proposed. The proposed method uses Particle Swarm Optimization (PSO) algorithm to determine the optimal MIMO antenna array topologies that can provide minimum entropy of the reconstructed image. According to the approach, a MIMO array is optimized with minimum entropy indicating high focusing quality.
    VL  - 4
    IS  - 2
    ER  - 

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Author Information
  • Department of Communication and Command, Chongqing Communication College, Chongqing, China

  • Department of Clinical Medicine, Chongqing Medical and Pharmaceutical College, Chongqing, China

  • Department of Communication and Command, Chongqing Communication College, Chongqing, China

  • Department of Communication and Command, Chongqing Communication College, Chongqing, China

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