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Increasing requirements in the field of security, in particular in the transport sector, the rescue work, the inviolability of private property and others urged to research work in the field of radar monitoring people, vehicles or other objects in the environment that not allow make so using the most popular and available technology for production and analysis of video images. These conditions of poor visibility, or even lack thereof, are darkness, bad weather, smoke, dust, wall (roof) buildings and the vehicle body. Existing instruments and special equipment occupy a certain niche in this area, mainly for counter-terrorism operations. However, such equipment is not readily available and extremely high price. In the paper presented research is development of the group’s existing radar technology in the field of location through opaque obstacles.

This document describes the results of the study contributing to the methods and tools applicable in plastic waste sorting systems that exploit the multistatic ultra-wideband impulse radar enforced with a deep learning signal processing back-end. The novelty of the research is the use of synthetic data for the development of a trained neural network before real data are available, and the use of a multistatic radar for the improvement of the training data set. The study results are described in multiple publications; the current paper shows the applicability of the described approach. The main results are as follows: a monostatic impulse radar can be used for the determination of material properties, such as thickness, dielectric permittivity, and losses, with limited accuracy; multistatic radar configuration increases the accuracy of the material property estimation; an open source finite difference time domain simulator can be used to simulate electromagnetic wave propagation in dielectric structures in order to generate synthetic data for development of optimized artificial neuron network structures used for the estimation of dielectric material properties, and the developed network can successfully be used for multistatic radar data processing. [ABSTRACT FROM AUTHOR]