Article 2317

Title of the article

DETECTION OF STOCHASTIC RADAR SIGNALS 

Authors

Popov Dmitriy Ivanovich, Doctor of engineering sciences, professor, sub-department of radioengineering systems, Ryazan State Radio Engineering University (59/1 Gagarina street, Ryazan, Russia), adop@mail.ru

Index UDK

621.391:621.396.96

DOI

10.21685/2072-3059-2017-3-2

Abstract

Background. The objects of the study are methods and algorithms for detecting stochastic radar signals against the background of normal white noise. The aim of the work is synthesize algorithms and design construction of appropriate structural schemes for detecting stochastic signals. 
Materials and methods. On the basis of the multidimensional probability density of signal samples at discrete instants of time, a description of the sequence of stochastic signals using the probability density functional is introduced. The method of investigation is statistical synthesis of detection algorithms using the operations of likelihood ratio calculation.
Results. As a result of calculating the likelihood ratio, an adaptive algorithm for detecting the sequence of stochastic signals against the background of normal white noise is synthesized and a scheme of the detector is given. An adaptive linear filter generates a reference signal from the observed oscillation, which is multiplied again by the received oscillation, and then integrated. The integration results are accumulated in the inter-period storage.
Conclusions. With a priori uncertainty of statistical characteristics of the signal (correlation function), the corresponding function is determined. It is transformed into an estimate of the inverse correlation function used in linear filter adaptation. The proposed modified detection algorithm and the corresponding detector scheme are similar to the energy receiver, in which the decisive statistics is the total energy of the received realizations previously passed through the adaptive linear filter.

Key words

adaptive detection algorithm, correlation matrix, correlation function, multi-dimensional probability density, normal white noise, inverse correlation matrix, inverse correlation function, likelihood ratio, stochastic signal

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References

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Дата создания: 06.02.2018 10:34
Дата обновления: 26.02.2018 14:49