Non-linear signal detection algorithms on background additive-multiplicative non-gaussian noise
DOI:
https://doi.org/10.15587/1729-4061.2012.5998Keywords:
radio signals detection, moment quality criterion, additive-multiplicative Non-Gaussian noiseAbstract
The problem of signal detection on the background noise is one of the most important and actual in many applications. The most complete model of the interaction of signals and noise is additive-multiplicative model, which is typical for many practical cases.
The task signal processing is more difficult when considering Non-Gaussian noise, both additive and multiplicative character. Therefore, the actual task is the development of methods and algorithms for statistical signal processing on the background additive-multiplicative Non-Gaussian noise in radar, sonar, geophysics, systems of mobile communications.
This paper illustrates the use of an alternative approach to the description of random variables - moment–cumulant description.
In this work the additional question of efficient algorithms for signal detection on a background additive-multiplicative Non-Gaussian noise are consider.
Purpose of work is improve the efficiency of systems Signal Detection on a background additive-multiplicative Non-Gaussian noise on the basis of polynomial decision rules, that are optimal for the moment criterion.
Presented synthesis of decision rules radiosignal detection on the background additive-multiplicative Non-Gaussian noise to the degree stochastic polynomial . It is shown that with increasing degree stochastic polynomial and considering Non-Gaussian noise, value of the criterion of the upper limit of probability of errors of the first and second kind decreases, indicating a decrease in the probability of errors synthesized nonlinear decision rules and increase their effectiveness in comparison with linear decision rulesReferences
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