Developing a graphical package for sensor arrays design, optimization and maintenance

  • Authors

    • Ahmed N. Jabbar University of Babylon
    • Ibrahim A. Murdas University of Babylon
    https://doi.org/10.14419/ijet.v7i3.14113

    Received date: June 14, 2018

    Accepted date: June 22, 2018

    Published date: July 8, 2018

  • 5G Technology, Uniform Sensor Arrays, Random Sensor Arrays, Evolutionary Algorithms, Sidelobes Reduction, Matlab Guide, Digitally Controlled Arrays.
  • Abstract

    The sensor arrays are now an essential part of any communication, medical and remote sensing system. These arrays should be designed with utmost performance to ensure the maximum link efficiency. The available commercial sensor arrays design packages are expensive, complicated and cannot be easily modified to accommodate the users’ needs. This work suggests a solution that is to design an open source specialized application to serve the ever-changing needs of the users. This package is called Sensor Array Design and Optimization (SADO) and it is developed to allow the unexperienced users and the researchers to design, test and optimize their sensor arrays using effi-cient optimization algorithms. The optimization is trying to reduce the sidelobe levels to reduce the interference. The application is simple and friendly to use, with professional graphical results. The predesigned arrays configurations supplied with this package are uniform and random arrays. The built in optimization algorithms are: Artificial Bee Colony (ABC), Biogeography-Based Optimization (BBO) and Teaching Learning Based Optimization (TLBO). The results for various designs and optimization results are also given and compared to indicate the best settings for the user. Some optimization ratios might reach about 50% that represent -3dB reduction in sidelobe level.

  • References

    1. C. Balanis, Antenna Theory Analysis and Design, John Wiley & Sons, Inc., Third Edition, USA, 2005.
    2. R. Haupt, Antenna Arrays a Computational Approach, John Wiley & Sons, USA, 2010. https://doi.org/10.1002/9780470937464.
    3. J. Hilbertsson and J. Magnusson, Simulation and Evaluation of an Active Electrically Scanned Array (AESA) in Simulink®, Chalmers University of Technology, 2009.
    4. H. Cher, Two-Way Pattern Design for Distributed Subarray Anten-nas, Master of Science in Engineering Science (Electrical Engineer-ing), Naval Postgraduate School, Monterey, California, 2012.
    5. V. Madisetti Editor in Chief, Wireless, Networking, Radar, Sensor Array Processing, and Nonlinear Signal Processing, CRC Press, USA, 2010.
    6. A. Brown, Electronically Scanned Arrays MATLAB® Modeling and Simulation, CRC Press, USA, 2012. https://doi.org/10.1201/b12044.
    7. A. N. Jabbar, “New Elements Concentrated Planar Fractal Antenna Arrays for Celestial Surveillance and Wireless Communications”, ETRI Journal, Volume 33, Number 6, December 2011, pp. 849–856. https://doi.org/10.4218/etrij.11.0111.0036.
    8. P. Gorman, Wideband Aperiodic Antenna Array Design with CMA-ES, M. Sc. Thesis in Electrical Engineering, Pennsylvania State Uni-versity, 2012.
    9. A. O'Donnell and R. McGwier, “Review of Modern Thinned Array Methods for Optimizing Randomly Scattered Elements”, United States National Committee of URSI National Radio Science Meeting (USNC-URSI NRSM), Boulder, CO, 2018, pp. 1–2.
    10. H. Jung and I.-H. Lee, “Secrecy Rate of Analog Collaborative Beamforming with Virtual Antenna Array Following Spatial Ran-dom Distributions”, IEEE Wireless Communications Letters, 2018. https://doi.org/10.1109/LWC.2018.2804389.
    11. H. Jung and I. H. Lee, “Analog Cooperative Beamforming with Spherically-Bound Random Arrays for Physical-Layer Secure Communications,” IEEE Communications Letters, Vol. 22, No. 3, March 2018, pp. 546–549. https://doi.org/10.1109/LCOMM.2017.2782807.
    12. J. Benveniste, Design and Development of a Single Channel RSNS Direction Finder, M. Sc. in Electrical Engineering, Naval Postgradu-ate School, Monterey, California, 2009.
    13. J. C. Chen, “Low-Complexity Constant Envelope Precoding Using Finite Resolution Phase Shifters for Multiuser MIMO Systems with Large Antenna Arrays,” IEEE Transactions on Vehicular Technolo-gy, (Early Access), 2018.
    14. Y. Xiong and G. Wang, “An X-Band 6-Bits Highly-Accurate Digi-tal-Stepped Phase Shifter MMIC for Phased Array System,” 3rd IEEE International Conference on Computer and Communications (ICCC), Chengdu, 2017, pp. 826–829.
    15. T. Biedka, Analysis and Development of Blind Adaptive Beamform-ing Algorithms, Ph. D. Thesis in Electrical Engineering, Blacksburg, Virginia, 2001.
    16. J. Brownlee, Clever Algorithms Nature-Inspired Programming Rec-ipes, Lulu.com, 2011.
    17. Home Page, https://abc.erciyes.edu.tr/.
    18. R. Parpinelli, C. Benitez and H. Lopes, Parallel Approaches for the Artificial Bee Colony Algorithm Handbook of Swarm Intelligence: Concepts, Principles and Applications, Series: Adaptation, Learning, and Optimization; Springer; 2011, pp: 329–346, Berlin, Germany.
    19. Y. Boudouaoui, H. Habbi and F. Harfouchi; Swarm Bee Colony Op-timization for Heat Exchanger Distributed Dynamics Approximation With Application to Leak Detection, Handbook of Research on Emergent Applications of Optimization Algorithms, IGI Global, 2017, pp: 557–578, , Hershey, PA, USA.
    20. D. Simon, “Biogeography-Based Optimization”, IEEE Transactions on Evolutionary Computation, Vol. 12, No. 6, 2008, pp: 702– 713. https://doi.org/10.1109/TEVC.2008.919004.
    21. H. Ma and D. Simon, Evolutionary Computation with Biogeogra-phy-based Optimization Vol. 8, Wiley & Sons, USA, 2017. https://doi.org/10.1002/9781119136507.
    22. R. Rao, Teaching Learning Based Optimization Algorithm and Its Engineering Applications, Springer, USA, 2016. https://doi.org/10.1007/978-3-319-22732-0.
    23. Parallel Computing Toolbox™ User's Guide, The MathWorks, Inc., USA, 2018.
    24. MATLAB® Graphics, the MathWorks, Inc., USA, 2018.
    25. Jameel, F. et. al., “Massive MIMO: A Survey of Recent Advances, Research Issues and Future Directions”, International Symposium on Recent Advances in Electrical Engineering (RAEE), 2017. https://doi.org/10.1109/RAEE.2017.8246040.
    26. Ancansa, G. et. al., “Spectrum Considerations for 5G Mobile Com-munication Systems”, Procedia Computer Science 104, Elsevier, 2017, pp. 509 – 516. https://doi.org/10.1016/j.procs.2017.01.166.
    27. IMT traffic estimates for the years 2020 to 2030 IMT. Report M.2370-0; 2015. p. 10–14.
    28. S. Orfanidis, Electromagnetic Waves and Antennas, Rutgers Univer-sity. http://www.ece.rutgers.edu/~orfanidi/ewa/, 2014.
    29. M. Bansal, Digital Control Board for Phased Array Antenna Beam Steering In Adaptive Communication Applications, M. Sc. in Electri-cal Engineering, California Polytechnic State University, USA, 2013.
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  • How to Cite

    N. Jabbar, A., & A. Murdas, I. (2018). Developing a graphical package for sensor arrays design, optimization and maintenance. International Journal of Engineering and Technology, 7(3), 1388-1399. https://doi.org/10.14419/ijet.v7i3.14113