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The method of improving the interference protection of axisymmetric antennas is considered. An experimental study of the focusing properties of a zonal antenna is carried out in this work. Such a zonal antenna acts as a shading screen and is located in the aperture of an axisymmetric antenna. The combination of a shading screen with an axisymmetric antenna can significantly reduce the level of side lobes in the anterior semi-space, and as a result, significantly improve the immunity of the antenna system. A zonal antenna for 40 GHz frequency is manufactured. The field distribution along the axis of symmetry for different numbers of rings in the antenna is experimentally investigated. The number of rings varied from 1 to 5. The focusing properties of the zonal antenna are studied at the change of operating frequency. The position of the focus is investigated when the working frequency changes in relation to the calculated frequency. It is established that the experimentally found focal point does not coincide with the focal point found by geometric optics. For a zonal antenna with three rings, the difference between the experimentally found focus and the focus found by the law of geometric optics is 0.1%. The distribution of the field in planes perpendicular to the focal line is investigated. It is established that an increase in the number of rings in a zonal antenna to more than five leads to diffraction effects which impair the focusing properties of the zonal antenna. At the same time there is a "deliquescence" of the wave beam in the focus. These studies allow us to determine the boundaries of the working frequency of a complex antenna system.

The problem of electromagnetic wave diffraction by the metal objects has been solved using integral equation technique. The diagrams of backward scattering have been plotted for four different objects. Based on the feature vector, which has been constructed by applying wavelet packet signal decomposition, a neural network has been trained. We have performed the testing of ability of the neural network to recognize the object depending on the noise level. Various methods of the feature vector forming have been considered.