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Information × Registration Number 0226U002840, (0124U000461) , R & D reports Title Methods of detection and identification of sources and scatters of electromagnetic waves in inhomogenious media popup.stage_title Алгоритми та обчислювальні методи розрахунку параметрів електромагнітних хвиль від високоенергетичних збудників природного та техногенного походження Head Dubinin Mykola M., Доктор філософії Registration Date 07-03-2026 Organization V.N. Karazin Kharkiv National University popup.description1 The goal of the project is the development and implementation of effective methods of detection and identification of sources and scatterers of electromagnetic signals in heterogeneous environments. Simulate and experimentally confirm the processes of propagation of electromagnetic waves in inhomogenious media containing various exciters, scatterers, disturbers and sources of electromagnetic waves, conduct research for various fixed frequencies and use the Fourier series decomposition approach for broadband signals. Take into account absorption and refraction at the boundaries of the separation of the medium and determine the location of the targets by the received signal in the receiver located outside the medium. Use machine learning algorithms to solve the inverse radiophysical problem of determining sources (or scattering objects) regardless of external factors. popup.description2 Within the reporting stage, a set of theoretical, numerical, and applied studies was carried out to advance ethods for detecting, localizing, and identifying electromagnetic wave sources and scatterers in inhomogeneous media. The physical problem statements were refined, informative signal parameters were identified, and modeling scenarios were developed for different types of media. Numerical simulations of the propagation and scattering of ultra-wideband pulsed waves were performed using the FDTD method. Based on the obtained data, the formation and processing of ground-penetrating radar B-scans were implemented with the application of Kirchhoff migration to reconstruct the spatial positions of concealed objects. The influence of local dielectric inhomogeneities on reconstruction accuracy was investigated, and the conditions for the correct application of processing procedures were determined. Neural network algorithms for automated object recognition under noisy conditions were developed and optimized. Training datasets were generated from simulated signals, and the impact of data structure and processing parameters on classification quality was analyzed. Configurations ensuring enhanced noise immunity were identified. The possibilities of three-dimensional positioning based on ultra-wideband signals and machine learning methods were studied, confirming the prospects for local navigation systems under limited satellite navigation availability. Analytical and numerical results were obtained on the formation and transformation of structured electromagnetic beams in waveguide resonator systems of the terahertz range. Regularities in the variation of transverse structure, phase characteristics, and energy redistribution during interaction with spiral phase elements were established. An analysis of electromagnetic processes in natural inhomogeneous media was conducted, allowing clarification of the features of geomagnetic field variations during extreme disturbances. Product Description popup.authors Vladyslav S. Seniuta Rolan D. Akhmedov Vadym A. Plakhtii Vladyslav S. Khrychov Mykyta B. Shevelev popup.nrat_date 2026-03-07 Close