ISSN 1991-2927
 

ACP № 1 (63) 2021

Author: "Konstantin Konstantinovich Vasilev"

Konstantin Konstantinovich Vasilev, Doctor of Sciences in Engineering; graduated from the Radioengineering Faculty of Leningrad Electrotechnical Institute n.a. V.I. Ulyanov (Lenin); Professor of the Department of Telecommunications at Ulyanovsk State Technical University, Honored Worker of Science and Technology of the Russian Federation, Corresponding Member of the Academy of Sciences of the Republic of Tatarstan; an author of monographs, manuals, and articles in the field of statistical synthesis and analysis of information systems. e-mail: vkk@ulstu.ruK. K. Vasilev,

Leonid Iurevich Korolev, graduated from Ogarev Mordovia State University; Postgraduate Student of the Department of Infocommunication Technologies and Communication Systems of Ogarev Mordovia State University; an author of articles in the field of the unmanned aerial vehicle navigation. e-mail: l.y.korolev@ yandex.ruL. I. Korolev

Opportunities for reduction of computational costs when determining the coordinates of autonomous vehicle group60_2.pdf

The article deals with the known and new algorithms proposed by authors for integrating the estimates of eigen and mutual coordinates and velocities of movement for an arbitrary number of autonomous vehicles. The impact of uncontrolled external disturbances on the system is taken into account. Four versions for developing the navigation-parameter processing algorithms on the basis of two-stage integration of observations, Kalman vector and scalar filters are proposed and examined. The first technique involves estimating the coordinates and speeds of all aerial vehicles with a Kalman vector filter. The second technique is to integrate velocities at the first stage and to use the Kalman vector filter at the second stage. The third one is based on separate integration of coordinates and velocities at the first stage with subsequent processing of estimates with a scalar Kalman filter. In the fourth technique, observations of eigen and mutual coordinates are integrated and processed by a scalar filter, taking into account direct observations of eigen speed of the apparatus. Expressions for covariance error matrices are derived, and the comparison results of the effectiveness of the considered approaches are given. Computational costs are analyzed when estimating the location by the use of each of the considered algorithms.

Integration of estimates, coordinates, state vector, observation model, stochastic equation, Kalman filter, covariance of errors.

2020_ 2

Sections: Automated control systems

Subjects: Automated control systems.



Konstantin Konstantinovich Vasilev, Doctor of Sciences in Engineering; graduated from the Radioengineering Faculty at Leningrad Electrotechnical Institute n.a. V.I. Ulyanov (Lenin) (“LETI”); Professor of the Department of Telecommunications at Ulyanovsk State Technical University; Honoured Worker of Science and Technology of the Russian Federation, Corresponding Member of the Academy of Sciences of the Republic of Tatarstan; an author of monographs, manuals, and articles in the field of statistical synthesis and analysis of information systems. e-mail: vkk@ulstu.ruK. K. Vasilev

Vitalii Evgenevich Dementev, Candidate of Sciences in Engineering, Associate Professor; graduated from the Faculty of Economics and Mathematics with the specialty in Applied Mathematics at Ulyanovsk State Technical University; Head of the Department of Telecommunications at UlSTU; an author of monographs and articles in the field of statistical synthesis and analysis of multidimensional images. e-mail: dve@ulntc.ruV. E. Dementev

Aleksei Vladimirovich Belianchikov, Postgraduate Studentofthe Departmentof Telecommunications at Ulyanovsk State Technical University; graduated from UlSTU with the Master’s degree in Infocommunication Technologies and Communication Systems; an author of publications in the field of information and communication systems. e-mail: friedlemon73@gmail.comA. V. Belianchikov

Receiving discrete messages in multi-frequency communication systems with pilot signals60_12.pdf

The optimal algorithm for receiving multi-position signals in multi-frequency communication systems with the estimation of quadrature components (CS) has been synthesized using the Bayesian approach. The algorithm is similar to the well-known quadratic-linear receiver, but differs in the presence of optimal CS estimates and parameter correction in its composition. The article considers possibilities of evaluating CS based on built-in pilot signals and image processing methods as well. Upon that autoregressive models with multiple roots of characteristic equations, which allow simulating quasi-isotropic fields, are suggested for approximating the real correlation functions of the CS fields. The study shows that the use of such models results in a slight increase in the variance of the reconstruction error with respect to the discrete Wiener filter, but allows using recurrent interpolation of random fields with minimal computational costs. The article describes conditions under which it is possible to make the simplest CS estimation based on observations of the nearest pilot signals.

Communication system, pilot signal, quadrature components, white noise, autoregression, correlation function, covariance matrix of estimates, Wiener filter, Kalman filter.

2020_ 2

Sections: Electrical engineering and electronics

Subjects: Electrical engineering and electronics.



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