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Synthesis of algorithms of non-linear adaptive signal processing for tracking meters using blocks of non-linear transformation with feed-back


V.M. Artyushenko – Dr. Sc. (Eng.), Professor, Head of Department of Information Technology and Management Systems, Technological University (Korolyov, Moscow region)
V.I. Volovach – Dr. Sc. (Eng.), Associate Professor, Head of Department of Information and Electronic Service, Volga Region State University of Service (Togliatti)

The issues associated with the synthesis of algorithms of adaptive nonlinear signal processing of the discriminators of tracking meters using the feed-back blocks of nonlinear transformation under the influence of non-Gaussian broadband noise and narrowband noise are considered and analyzed. It is shown that in real cases, the useful signal is affected by non-Gaussian noise with unknown density of distribution of instantaneous values or its envelope. Non-linear processing of the received signal in these cases should be adaptive, self-consistent with probabilistic properties of influencing noise and with current mismatch between the measured parameters and their estimates.
It is shown that the feedback adaptive blocks of nonlinear transformation (ABNT) should be used if the dependence between the am-plitude characteristic (AC) of the block and the settings is non-linear. It also should be used to reduce the impact of uncontrolled external disturbances. Feed-back ABNTs are divided into two groups: with iterative probabilistic algorithms being used and with the coefficient of noise suppression measured.
The implementation of ABNT with feedback and with iterative probabilistic algorithms used under the influence of non-Gaussian broadband noise and narrowband noise is presented. The results of mathematical modeling of ABNT with polygon amplitude charac-teristics and a probabilistic iterative algorithm with using Lagrange function when exposed to noise with Rice distribution or lognormal distribution of the envelope are shown; the convergence of the adaptation algorithm with the probability equal to one is shown.
We analyzed the implementation of ABNT with feedback and measuring the coefficient of noise suppression, as in the previous case, under the influence of non-Gaussian broadband noise and narrowband noise. The functional diagram of noise samples processing under the influence of broadband noise is shown; it is shown that the obtained estimator of the coefficient of noise suppression is consistent and asymptotically unbiased. The conditions of correct operation of the measuring algorithm are defined, and its accuracy is illustrated on the example of Gaussian noise. The algorithms for finding a local extremum of the optimal controller are shown. The algorithm for finding the global maximum is defined and the results of its simulation are presented which indicate a good convergence of the algorithm.
It is shown that the objective of feedback ABNT is to achieve the maximum coefficient of noise suppression and monitor it when probabilistic properties of affecting noise change or in the presence of external disturbances.

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