Mathematical Modeling of the Electrophysical Properties of a Layered Nanocomposite Based on Silicon with an Ordered Structure

The authors carried out modeling of the electrophysical properties of composite media. The frequency dependences of the dielectric constant on the type of inclusions in the composite are investigated. On the basis of the nanocomposite considered in the work, based on Si, B, and SiO2, the authors model a reflecting screen, the lattice elements of which have a layered hierarchically constructed structure similar to a fractal formation. The influence of the level of fractality on the optical properties of the object was also investigated, and it was found that the proposed structure makes it possible to increase the operating frequency range of the reflecting screen and the efficiency, in comparison with reflecting screens that have a lattice of traditional structure. The results obtained can be of practical interest for broadband and nonlinear radar devices, localization devices and mobile objects, microelectronics, as well as intelligent applications in the field of information security.

Adaptive Matching of the Radar Signal and Image Display Device Dynamic Ranges

This article presents nonlinear radar signal processing method to form an image of the Earth's surface. The method proposes to match the dynamic ranges of the received signal and of the visualization device. The essence of the method is adaptive nonlinear signal processing, which provides better local contrast of radar images and improves discrimination of individual objects. The computational complexity of the proposed algorithm is optimized and allows real-time implementation in the airborne computing systems with limited computational power. Objects with large RCS merged into large illuminated "spots"; their visibility on the surrounding background has been reduced, unwanted effects are due to the fact that the above algorithms have a single point effect. To overcome the problems, the «Retinex» algorithm is usually used. They do not take into account the local neighborhood of pixels; therefore, in cases where the image contains both highly dark and strongly light local areas, these algorithms cannot provide high-quality matching of dynamic ranges.