MATEC Web Conf.
Volume 132, 2017XIII International Scientific-Technical Conference “Dynamic of Technical Systems” (DTS-2017)
|Number of page(s)||5|
|Section||Cognitive methods of heterogeneous data analysis|
|Published online||31 October 2017|
The combined maximum principle in the problem of synthesis of an adaptive dynamic filter under conditions of disturbances in the measurement process
1 Rostov State Transport University, 344038, Rostov-on-Don, Russia
2 Don State Technical University, 344002, Rostov-on-Don, Russia
* Corresponding author: firstname.lastname@example.org
The article considers the problem of estimating the parameters of motion under conditions of disturbances in the measurement process, which are caused by missing data, misses in measurements, etc. in the operation of radar systems. The structure of the included filter for estimating the parameters of motion is determined by the mathematical model of the maneuvering target. At present time the kinematic models are widely used, but they do not fully correspond to the observed dynamics. This may lead to divergence of the estimation process and failure of the computational procedure. New dynamic filters of the combined maximum principle with the dynamic model of motion possess higher accuracy and stability and smaller amount of computational costs in comparison with common filters. The materials and methods We propose new mathematical model that determines the structure of the dynamic filter of the combined maximum principle. A numerical simulation of the operation of the proposed filter, as well as comparison of its efficiency with common filters by a number of criteria are performed. The results. The efficiency of functioning of radio engineering systems on the basis of the solution to the problem of synthesis of a dynamic filter using method of the combined maximum principle with construction of adaptive dynamic model of motion in vector-matrix form is increased. This makes it possible to eliminate the divergence of computational estimation procedures caused by the inadequacy of the structure of the mathematical model of motion. It is shown that the developed dynamic filter differs from the known filters in terms of the structure of the transition matrix. Discussion and conclusions The results of the mathematical modeling showed that in comparison with the Kalman filter and the “alpha-beta” filter the new dynamic filter under conditions of disturbances in the measuring process increase the number of performance indicators.
© The Authors, published by EDP Sciences, 2017
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (http://creativecommons.org/licenses/by/4.0/).
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