Method of interception of small and inconspicuous unmanned aerial vehicles


DOI: 10.34759/trd-2023-129-21

Аuthors

Sentsov A. A.1*, Polyakov V. B.1, Ivanov S. A.2, Pomozova T. G.1**

1. Saint Petersburg State University of Aerospace Instrumentation, 67, Bolshaya Morskaya str., Saint Petersburg, 190000, Russia
2. Saint-Petersburg State University of Economics, 21, Sadovaya str., Saint-Petersburg, 191023, Russia

*e-mail: toxx@list.ru
**e-mail: pomozova-tatyana@yandex.ru

Abstract

As of today, the onrush development of the unmanned aviation and of its application scope are observed. Besides the application in economic activity, the scope of the unmanned aviation functions by special services and in military sphere is constantly growing. The small-sized and nearly invisible unmanned aerial vehicles present are of special peril. The problem of low-observable targets detecting, tracking and intercepting for the socially significant objects protecting occurs. The article proposes a method for integration of the unmanned aviation detection, tracking and intercepting managing means, as well as synchronization of the control for these tasks solving. The article presents the description of the open information transfer protocol used in a wireless two-way exchange channel for the interception means control. Classes of possible interception objects and the structure of the complex for the interception process organization are determined. The article proposes scenarios of interception options, and presents their time characteristics as well as describes the options for radar stations that ensure detection of small-sized and low-observable objects with low values of the effective scattering area. The article describes the currently up-to-date task of identifying features of the aerial objects observed by radar for recognition and decision-making with the allocation of classes of artificial and natural origin as well. The article defines methods of useful data extracting from the reflected signals employing a convolutional neural network, and considers two options of neural network structuring, in which the input data is represented as a graphical representation of the spectrum of the reflected signal (in grayscale) and in the form of arrays of numbers.

Keywords:

radar station, unmanned aerial vehicle, unmanned aircraft, detection of aerial objects, neural network

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