Abstrakt
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 wellsuited 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.
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Autorzy (6)
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- Wersja publikacji
- Accepted albo Published Version
- Licencja
- Copyright (2019 IEEE)
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Informacje szczegółowe
- Kategoria:
- Aktywność konferencyjna
- Typ:
- publikacja w wydawnictwie zbiorowym recenzowanym (także w materiałach konferencyjnych)
- Język:
- angielski
- Rok wydania:
- 2019
- Opis bibliograficzny:
- Tarkowski M., Burtowy M., Rzymowski M., Nyka K., Groth M., Kulas Ł.: Improved RSS-Based DoA Estimation Accuracy in Low-Profile ESPAR Antenna Using SVM Approach// / : , 2019,
- DOI:
- Cyfrowy identyfikator dokumentu elektronicznego (otwiera się w nowej karcie) 10.1109/etfa.2019.8868967
- Bibliografia: test
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- 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. otwiera się w nowej karcie
- L. Kulas, "RSS-based DoA Estimation Using ESPAR Antennas and Interpolated Radiation Patterns," IEEE Antennas Wireless Propag. Lett., vol. 17, pp.25-28, 2018. otwiera się w nowej karcie
- S. Chandran, Advances in Direction-of-Arrival Estimation. London, U.K.: Artech House, 2005.
- Rzymowski, P. Woznica, and L. Kulas, "Single-Anchor Indoor Localization Using ESPAR Antenna," IEEE Antennas Wireless Propag. Lett., vol. 15, pp. 1183-1186, 2016. otwiera się w nowej karcie
- 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. otwiera się w nowej karcie
- 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. otwiera się w nowej karcie
- 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. otwiera się w nowej karcie
- 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. otwiera się w nowej karcie
- Aurelien Geron, Hands-On Machine Learning with Scikit-Learn & TensorFlow. Sebastopol, CA: O'Reilly Media, Inc., 2017, pp. 156-165 otwiera się w nowej karcie
- 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. otwiera się w nowej karcie
- C. Chang and C. Lin, LIBSVM: a library for support vector machines, 2001. otwiera się w nowej karcie
- 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. otwiera się w nowej karcie
- Źródła finansowania:
- Weryfikacja:
- Politechnika Gdańska
wyświetlono 106 razy