SYNTHESIS OF NONPARAMETRIC ALGORITHMS FOR DETECTION OF RADAR CORRELATED SIGNALS AGAINST THE BACKGROUND OF MARKOV CORRELATED NOISE

Authors

  • I. G. Prokopenko National Aviation University, Kyiv

DOI:

https://doi.org/10.18372/1990-5548.62.14376

Keywords:

Signal processing, robust rank algorithms, radar signal detection, Markov correlated noise, aproristick uncertainity

Abstract

The article deals with the technology of construction of nonparametric processing methods of correlated random processes. The use of a Markov model of correlated signals allows to synthesize the nonparametric rank algorithms that use nonparametric estimation of a one-dimensional cumulative distribution function using  a training sample containing interference only. The theory of synthesis of nonparametric rank Markov decision rules is constructed, the problem of synthesis of rank nonparametric algorithm for detection of  correlated signal against the background of uncorrelated noise  on the output of amplitude demodulator is solved. Property of this algorithm is investigated.

Author Biography

I. G. Prokopenko, National Aviation University, Kyiv

Aviation Radioelectronic Complexes Department

Doctor of Engineering Science. Professor

orcid.org/0000-0003-4169-3774

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Issue

Vol. 4 No. 62 (2019)

Section

THEORY AND METHODS OF SIGNAL PROCESSING

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