Subsurface object recognition by ultrawideband radar and artificial neural networks
Abstract
The problem of underground object recognition is solved by the use of artificial neural network that analyses the characteristics of reflected impulse electromagnetic field. The surface of ground which hides a perfectly conducted object is irradiated by ultrawideband plane wave with Gaussian time form. The time dependences of reflected field above the ground surface are received by means of finite difference time domain method. The normalized amplitudes of electric component of field in definite points of observation calculated for constant time step are used as input data for multilayer artificial neural network. Metal tube under the ground surface buried at different depths is considered as an example of the object for investigation.
Downloads
References
Turk A. S., Hocaoglu K. A., Vertiy A. A. Subsurface Sensing, Ho-boken: Wiley, 2011.
Taylor J. D. Ultrawidebandradar: applications and design, Boca Raton, London, NewYork: CRC Press, 2012.
Harmuth H. F., Boules R. N., Hussain M. G. M. Electromagnetic signals: reflection, focusing, distortion, and their practical applications. NewYork: Kluwer Academic, Plenum Publishers, 1999.
Immoreev I., Samkov S., Teh-HoTao, Short-Distance Ultra-Wideband Radars // IEEE Aerospace and Electronic Systems Magazine, Vol. 20, No. 6, 2005, P. 9–14.
Daniels D. J. Ground penetrating radar, 2nd ed., London: IEEE, 2004.
Cook J. C. Proposed monocycle-pulse very high frequency radar for airborne ice and snow measurement // Trans. AIEE Commun. Electron., No. 79, 1960, P. 588–594.
Pochanin G., Masalov S., Pochanina I., Capineri L., Falorni P., Bechtel T. Modern Trends in Development and Application of the UWB Radar Systems // Proc. 8th International Conference on Ultrawideband and Ultrashort Impulse Signals, Odessa, Ukraine, pp. 7–11, 5-11 September 2016,
Hubel D. H., Wiesel T. N. Receptive fields, binocular interaction, and functional architecture in the cat’s visual cortex // Journal of Physiology, London, 1962, vol. 160, P. 106–154.
Hebb D. Organization of behaviour, New York, J. Wiley, 1949.
Хайкин С. Нейронные сети: полный курс, 2-е изд., испр. : Пер. с англ. – М. : ООО «И.Д. Вильямс», 2006. –1104с.
Широкорад Д.В., Думин А.Н., Думина О.А., Катрич В.А. Анализ импульсных полей, отраженных от слоистой среды с потерями, с помощью искусственной нейронной сети // Вісник Харківського національного університету імені В.Н. Каразіна. Радіофізика та електроніка. – 2009. – Вип. 15. – №883. – С.35–40.
Taflove A., Hagness S. Computational Electrodynamics: The Finite-Difference Time-Domain Method, 3rd ed., Boston, London: Artech House, 2005.
Катрич В.А., Думин А.Н. Излучение нестационарных полей из открытого конца прямоугольного волновода // Изв. ВУЗов. Радиоэлектроника. – 2003. – Т.46, №11. – С.34–42.
