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Saint Petersburg, Russia

Markov E.,Mozhaisky Military Space Academy
Journal of Applied Remote Sensing | Year: 2016

Unmanned aerial vehicles (UAVs) have become used increasingly in earth surface observations, with a special interest put into automatic modes of environmental control and recognition of artificial objects. Fractal methods for image processing well detect the artificial objects in digital space images but were not applied previously to the UAV-produced imagery. Parameters of photography, on-board equipment, and image characteristics differ considerably for spacecrafts and UAVs. Therefore, methods that work properly with space images can produce different results for the UAVs. In this regard, testing the applicability of fractal methods for the UAV-produced images and determining the optimal range of parameters for these methods represent great interest. This research is dedicated to the solution of this problem. Specific features of the earth's surface images produced with UAVs are described in the context of their interpretation and recognition. Fractal image processing methods for extracting artificial objects are described. The results of applying these methods to the UAV images are presented. © 2016 Society of Photo-Optical Instrumentation Engineers (SPIE). Source

Usychenko V.G.,Polytechnic University of Mozambique | Sasunkevich A.A.,Mozhaisky Military Space Academy | Sorokin L.N.,Polytechnic University of Mozambique
Journal of Communications Technology and Electronics | Year: 2016

A numerical model, as well as a simpler analytical one, which describe heat accumulation in microwave semiconductor devices exposed to high-power electric-pulse trains, are constructed. Conditions are estabtished under which heat is accumulated with each subsequent pulse up to the onset of a catastrophic failure caused by the device burnout. It demonstrated that short-pulse trains with a small pulse period-topulse duration ratio are most dangerous. © 2016, Pleiades Publishing, Inc. Source

Novikov P.A.,Saint Petersburg State University | Khomonenko A.D.,Saint Petersburg State University | Yakovlev E.L.,Mozhaisky Military Space Academy
ACM International Conference Proceeding Series | Year: 2015

Indoor Mobile navigation systems are becoming more widespread in many areas (transport, public institutions, logistics and others.). It is becoming popular navigation based on fingerprint radio access points Wi-Fi. As a mechanism for storing and processing the radio fingerprint is often considered a model of artificial neural networks (ANN). The paper examines the main issues related to the creation of complex programs for indoor mobile navigation using neural networks. We justify the choice of AAN learning algorithms for an indoor mobile navigation system. © 2015 ACM. Source

Kuznetsov V.I.,Mozhaisky Military Space Academy | Danilova T.V.,Mozhaisky Military Space Academy
Cosmic Research | Year: 2011

An onboard astronomical system is suggested, based on the developed method using virtual measurements of zenith distances of stars. Two algorithms of the method are described, their theory is given, and statistical results of the system's simulation are presented. © 2011 Pleiades Publishing, Ltd. Source

Eremeev M.A.,Mozhaisky Military Space Academy | Gorbachev I.E.,Mozhaisky Military Space Academy
Automatic Control and Computer Sciences | Year: 2015

This paper presents an approach for the information security analysis of automated systems. The random behavior of new vulnerabilities that occur in the automated system in the process of operation is investigated. The formalization required to evaluate information security, which is based on the methods of the stochastic indication theory, is presented. © 2015, Allerton Press, Inc. Source

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