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Estimation of accuracy for information signal parameters measuring under simultaneous multiplicative and additive non-Gaussian noise

Keywords:

V.M. Artyushenko – Dr. Sc. (Eng.), Professor, Head of Department of Information Technology and Management Systems, Technological University (Korolyov, Moscow region)
E-mail: artuschenko@mail.ru
V.I. Volovach – Dr. Sc. (Eng.), Associate Professor, Head of Department of Information and Electronic Service, Volga Region State University of Service (Togliatti)
E-mail: volovach.vi@mail.ru


The issues of estimating the accuracy of measurement of the information parameters of the signal under the simultaneous influence of both multiplicative and additive non-Gaussian noise are considered and analysed. It is shown that in real cases, the useful signal is affected by not only additive noise with a Gaussian probability density function (PDF), but also additive and multiplicative noise with non-Gaussian distribution (or with an arbitrary PDF). In this case the Cramer-Rao lower bound is used to determine quantitative estimates of the measured parameter.
The accuracy of measurement of information parameters of the signal influenced by multiplicative noise of quasideterministic (deter-ministic) nature is estimated. The estimator is obtained by defining the generalized signal-to-noise ratio (SNR) and the variance of an unbiased estimator. It is shown that in the above case additional information can be received from modulating noise, which can be used to reduce the variance of an estimator of a measured parameter. It is also shown that the accuracy of measurement of the information parameter is influenced by the non-Gaussian nature of additive noise and by the average power of multiplicative noise. However, the increase of the average power of multiplicative noise leads to the decrease of influence of non-Gaussian nature of additive noise on the accuracy of measurement of the mentioned parameter.
The accuracy of information parameters of the signal is estimated when multiplicative noise is of random nature, also when using the SNR with the background of additive-multiplicative non-Gaussian noise of independent nature and with the variance of an unbiased estimator. In this case the potential accuracy of measurement can be by an order of magnitude smaller if the useful signal is influenced by multiplicative noise. It is shown that part of modulating noise should be considered as additional additive noise, which results in the decrease of the generalized SNR, including the case when the variance of this additive noise increases, thus the accuracy of an estimated parameter will be worse. It is shown that the increase in variance of non-Gaussian equivalent noise leads to a significant reduction in potential accuracy, but the increase in the coefficient of difference between the PDF of equivalent noise from Gaussian noise, leads to the improvement in measurement accuracy.

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