10.14489/vkit.2014.12.pp.010-017 |
DOI: 10.14489/vkit.2014.12.pp.010-017 Бухалёв В. А., Болдинов В. А., Прядкин С. П., Скрынников А. А. Аннотация. Рассмотрена задача оптимального комплексирования информации, поступающей от измерителя выходного сигнала линейной стохастической системы и индикатора случайно изменяющихся помеховых ситуаций. Получен байесовский рекуррентный алгоритм, основанный на теории систем со случайной скачкообразной структурой, марковской математической модели и двухмоментной параметрической аппроксимации с помощью распределений Пирсона первого типа. Алгоритм осуществляет взаимосвязанное и одновременное распознавание помеховых ситуаций и оценивание величины полезного сигнала. Ключевые слова: система со случайной скачкообразной структурой; марковская цепь; двухмоментная параметрическая аппроксимация; байесовский алгоритм; распределение Пирсона.
Bukhalev V. A., Boldinov V. A., Pryadkin S. P., Skrynnikov A. A. Abstract. The article is devoted to the problem of constructing optimal algorithms of complex information processing. Linear stochastic system and the indicator of situations of randomly changing disturbances are considered. The algorithm is based on the methods of Markov theory to the estimation of random processes. Unlike most algorithms based only on signal filtering, mentioned algorithm is focused on the more difficult task: detection, recognition and estimation of true signal-to-noise ratio. Feature of traditional methods of solving such tasks are chronologically sequential scheme of building “detection – recognition – estimation”. This approach is used in the methods of synthesis algorithms of information processing, based on the systems theory with Random Jumping Structure (RJS). Despite similarities between the true and false signals generated by modern means of information countermeasures, there are distinctive characteristics that can’t be simulated easily. This characteristic is, for example, the probability distribution of signals. Another characteristic feature is situations of randomly changing disturbances, due to two main reasons: the need to perform electromagnetic compatibility of signals during operation of measurement and information systems and the emergence of a system of random abrupt transients, reucing the effectiveness of its work.This article examines three possible typical situations of the disturbances, when the output signal of the measuring element contains only noise (false signal), only useful (true) signal, half the sum of true and false signals. It is assumed that the measured signal is filtered from noise and disturbances of natural origin with traditional algorithms for linear or non-linear filtering. The goal is to build approximately-optimal algorithm of information processing based on the following concepts: systems theory with RJS, Markov mathematical models, Bayesian approach, two-moment parametric approximation of probability density distributions by Pearson 1st type. Inputs of the algorithm are the measured signal and structure indicator reading, output signals are the probability of the situations of disturbances (structure), estimation of the structure state, estimation of the true signal and its variance. The approach demonstrated in the article proved its effectiveness, as it leads to an acceptable compromise between two conflicting requirements – accuracy of the solution and ease of implementation. Keywords: Systems theory with random jumping structure; Markov chain; Two-moment parametrical approximation; Bayesian algorithm; Distribution of Pearson.
РусВ. А. Бухалёв (ЗАО «Московский научно-исследовательский телевизионный институт»)
EngV. A. Bukhalev (CJSC «Moscow Scientific Research Television Institute»)
Рус1. Бухалёв В. А. Основы автоматики и теории управления. М.: ВВИА им. Н. Е. Жуковского, 2006. 406 с. Eng1. Bukhalev V. A. (2006). Automation basics and con-trol theory. Moscow: VVIA im. N. E. Zhukovskogo.
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