A Classifying Algorithm for Radar Signals Using the Wigner-Ville Distribution and the RBF Probability Density Function Estimator

Author

Grishin, Yuri P. ; Konopko, Krzysztof

Author_Institution

Prof., Bialystok Technical University, Electrical Engineering Faculty, ul. Wiejska 45D, 15-351 BiaÂ¿ystok, Poland. phone: +48 85 7469418, fax: +48 85 7469400, e-mail: ypg@pb.bialystok.pl

fYear

2006

fDate

24-26 May 2006

Firstpage

1

Lastpage

4

Abstract

A radar signal recognition can be accomplished by exploiting the particular features of modulation presented in a radar signal observed in presence of noise. These modulation features are the result of slight radar component variations and acts as an individual signature of a radar. The paper describes a radar signal classification algorithm based on using the Wigner-Ville Distribution (WVD), noise reduction procedure with using a two-dimensional filter and the RBF neural network probability density function estimator which extracts the features vector used for the final radar signal classification. The numerical simulation results for the P4-coded signals are presented.

Keywords

Classification algorithms; Feature extraction; Noise reduction; Pattern classification; Probability density function; Radar imaging; Radar signal processing; Signal processing algorithms; Signal representations; Time frequency analysis;

fLanguage

English

Publisher

ieee

Conference_Titel

Radar Symposium, 2006. IRS 2006. International

Conference_Location

Krakow, Poland

Print_ISBN

978-83-7207-621-2

Type

conf

DOI

10.1109/IRS.2006.4338031

Filename

4338031