AN INVESTIGATION OF SIDE LOBE SUPPRESSION IN INTEGRATED PRINTED ANTENNA STRUCTURES WITH 3D REFLECTORS

The paper discusses the problem of side lobe suppression in the radiation pattern of printed antenna arrays with different 3D reflector surfaces. The antenna array of eight symmetrical pentagonal dipoles with corner reflectors of various angles is examined. All investigated antenna arrays are fed by the same feeding network of impedance transformers enabling necessary amplitude distribution. Considering the different reflector surfaces, the influence of parasitic radiation from feeding network on side lobe suppression is studied to prevent the reception of unwanted noise and to increase a gai

NUMERICAL CALCULATION OF SHIELDING EFFECTIVENESS OF ENCLOSURE WITH APERTURES BASED ON EM FIELD COUPLING WITH WIRE STRUCTURES

In this paper a shielding effectiveness of protective metal enclosure with apertures and receiving antenna placed inside is numerically considered. The purpose of antenna, here considered as a dipole, is to detect the electromagnetic (EM) field level within the enclosure and to transfer this information via a coaxial cable to network analyzer. This follows the experimental procedure used to measure the shielding effectiveness of enclosure. Numerical model, based on the Transmission-Line Matrix (TLM) method and enhanced with so-called wire node, is used to simulate this experimental setup in order to investigate how much the antenna/cable presence underestimates the level of shielding effectiveness due to their two-way coupling with EM field inside enclosure. The numerical model is first verified with experimental results available in literature and then used to estimate the influence of radius and length of dipole-receiving antenna and the impact of cable presence on the distribution of EM field inside the enclosure and resonant frequencies shift

Efficient DoA Tracking of Variable Number of Moving Stochastic EM Sources in Far-Field Using PNN-MLP Model

An efficient neural network-based approach for tracking of variable number of moving electromagnetic (EM) sources in far-field is proposed in the paper. Electromagnetic sources considered here are of stochastic radiation nature, mutually uncorrelated, and at arbitrary angular distance. The neural network model is based on combination of probabilistic neural network (PNN) and the Multilayer Perceptron (MLP) networks and it performs real-time calculations in two stages, determining at first the number of moving sources present in an observed space sector in specific moments in time and then calculating their angular positions in azimuth plane. Once successfully trained, the neural network model is capable of performing an accurate and efficient direction of arrival (DoA) estimation within the training boundaries which is illustrated on the appropriate example

Nikola Tesla’s contributions to radio developments

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Application of metamaterials for the microwave antenna realizations

In this paper, the application of left-handed metamaterials for the realization of microwave antennas has been considered. Special emphasis is placed on lens antennas based on gradient-index metamaterials, and their advantages and enhanced features in comparison with conventional microwave antennas are highlighted

Digital filter-based 1D TLM model of dispersive anisotropic conductivity panel

One-dimensional (1D) Transmission Line Matrix (TLM) method with Z-transforms, is applied in the paper to allow for an efficient time-domain simulation of thin anisotropic conductive panel of dispersive behavior. It uses a digital filter model to incorporate the scattering coefficients of the panel at two TLM cells interface in order to avoid a fine meshing of panel thickness. Model validation is done for a panel made of carbon-fibre material whose electric conductivity is anisotropic and assumed to be frequency dependent according to the Drude model. Fine TLM mesh results are used to verify the model accuracy. [Projekat Ministarstva nauke Republike Srbije, br. TR32024

Some Applications of Neural Networks in Microwave Modeling

Abstract –This 1 paper presents some apprilcations of neural networks in the microwave modeling. The applications are related to modeling of either passive or active structures and devices. Modeling is performed using not only simple multilayer perceptron network (MLP) but also advanced knowledge based neural network (KBNN) structures. Keywords–Neural network, modeling, microwave, microstrip gap, microwave cavity, microwave transistor, noise parameters, scattering parameters. I