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Improved RSS-Based DoA Estimation Accuracy in Low-Profile ESPAR Antenna Using SVM Approach

Abstract

In this paper, we have shown how the overall performance of direction-of-arrival (DoA) estimation using lowprofile electronically steerable parasitic array radiator (ESPAR) antenna, which has been proposed for Internet of Things (IoT) applications, can significantly be improved when support vector machine (SVM) approach is applied. Because the SVM-based DoA estimation method used herein relies solely on received signal strength (RSS) values recorded at the antenna output port for different directional radiation patterns produced by the antenna steering circuit, the algorithm is well-suited for IoT nodes based on inexpensive radio transceivers. Measurement results indicate that, although the antenna can provide 8 unique main beam directions, SVM-based DoA of unknown incoming signals can successfully be estimated with good accuracy in a fast way using limited number of radiation patterns. Consequently, such an approach can be used in efficient location-based security methods in Industrial Internet of Things (IIoT) applications.

Acknowledgement: This paper is a result of the SCOTT project (scott-project.eu) which has received funding from the Electronic Component Systems for European Leadership Joint Undertaking under grant agreement No 737422. This Joint Undertaking receives support from the European Union’s Horizon 2020 research and innovation programme and Austria, Spain, Finland, Ireland, Sweden, Germany, Poland, Portugal, Netherlands, Belgium, Norway.

The document reflects only the authors' view and the Commission is not responsible for any use that may be made of the information it contains.

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Category:
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Type:
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Title of issue:
2019 24th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA)
Publication year:
2019
DOI:
Digital Object Identifier (open in new tab) 10.1109/etfa.2019.8868967
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  1. Yanchao Zhang, Wei Liu, Wenjing Lou and Yuguang Fang, "Location- based compromise-tolerant security mechanisms for wireless sensor networks," in IEEE Journal on Selected Areas in Communications, vol. 24, no. 2, pp. 247-260, Feb. 2006.
  2. A. Alsadi and S. Mohan, "Improving the Physical Layer Security of the Internet of Things (IoT)," 2018 IEEE International Smart Cities Conference (ISC2), Kansas City, MO, USA, 2018, pp. 1-8. open in new tab
  3. F. Viani, L. Lizzi, M. Donelli, D. Pregnolato, G. Oliveri, and A. Massa, "Exploitation of parasitic smart antennas in wireless sensor networks," Journal of Electromagnetic Waves and Applications, vol. 24, no. 7, pp. 993-1003, Jan. 2010. open in new tab
  4. M. Tarkowski, M. Rzymowski, L. Kulas and K. Nyka, "Improved Jamming Resistance Using Electronically Steerable Parasitic Antenna Radiator," 17th International Conference on Smart Technologies (EUROCON 2017), pp. 496-500, Jul. 2017. open in new tab
  5. L. Kulas, "RSS-based DoA Estimation Using ESPAR Antennas and Interpolated Radiation Patterns," IEEE Antennas Wireless Propag. Lett., vol. 17, pp.25-28, 2018. open in new tab
  6. S. Chandran, Advances in Direction-of-Arrival Estimation. London, U.K.: Artech House, 2005.
  7. Rzymowski, P. Woznica, and L. Kulas, "Single-Anchor Indoor Localization Using ESPAR Antenna," IEEE Antennas Wireless Propag. Lett., vol. 15, pp. 1183-1186, 2016. open in new tab
  8. M. Burtowy, M. Rzymowski, and L. Kulas, "Low-Profile ESPAR Antenna for RSS-Based DoA Estimation in IoT Applications," IEEE Access, vol. 7, pp. 17403-17411, 2019. open in new tab
  9. M. Tarkowski and L. Kulas, " RSS-based DoA Estimation for ESPAR Antennas Using Support Vector Classification," IEEE Antennas Wireless Propag. Lett., vol. 18, no. 4, pp. 561-565, Apr. 2019. open in new tab
  10. M. Tarkowski, M. Rzymowski, K. Nyka and L. Kulas, "RSS-Based DoA Estimation with ESPAR Antennas Using Reduced Number of Radiation Patterns," in Proc. 13th Eur. Conf. Antennas Propag. (EuCAP 2019), Cracow, PL, 2019, in press. open in new tab
  11. F. Melgani and L. Bruzzone, "Classification of hyperspectral remote sensing images with support vector machines," in IEEE Trans. Geosci. Remote Sens., vol. 42, no. 8, pp. 1778-1790, Aug. 2004. open in new tab
  12. Aurelien Geron, Hands-On Machine Learning with Scikit-Learn & TensorFlow. Sebastopol, CA: O'Reilly Media, Inc., 2017, pp. 156-165 open in new tab
  13. M. Plotka, M. Tarkowski, K. Nyka, and L. Kulas, "A Novel Calibration Method for RSS-Based DoA Estimation Using ESPAR Antennas," 22nd International Conference on Microwaves, Radar and Wireless Communications (MIKON 2018), Poznan, PL, 2018, pp. 65-68. open in new tab
  14. C. Chang and C. Lin, LIBSVM: a library for support vector machines, 2001. open in new tab
  15. This work was supported by SCOTT (www.scott-project.eu) project that has received funding from the Electronic Component Systems for European Leadership Joint Undertaking under grant agreement No 737422. This Joint Undertaking receives support from the European Union's Horizon 2020 research and innovation programme and Austria, Spain, Finland, Ireland, Sweden, Germany, Poland, Portugal, Netherlands, Belgium, Norway. open in new tab
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