DocumentCode
3308824
Title
Radar signal recognition based on time-frequency representations and multidimensional probability density function estimator
Author
Konopko, Krzysztof ; Grishin, Yuri P. ; Janczak, Dariusz
Author_Institution
Fac. of Electr. Eng., Bialystok Univ. of Technol., Bialystok, Poland
fYear
2015
fDate
10-12 June 2015
Firstpage
1
Lastpage
6
Abstract
A radar signal recognition can be accomplished by exploiting the particular features of a radar signal observed in presence of noise. The features are the result of slight radar component variations and acts as an individual signature. The paper describes radar signal recognition algorithm based on time frequency analysis, noise reduction and statistical classification procedures. The proposed method is based on the Wigner-Ville Distribution with using a two-dimensional denoising filter which is followed by a probability density function estimator which extracts the features vector. Finally the statistical classifier is used for the radar signal recognition. The numerical simulation results for the P4-coded signals are presented.
Keywords
Wigner distribution; probability; radar signal processing; Wigner-Ville distribution; multidimensional probability density function estimator; noise reduction; radar signal recognition; statistical classifier; time-frequency representations; two-dimensional denoising filter; Algorithm design and analysis; Feature extraction; Noise; Noise reduction; Radar; Signal processing algorithms; Time-frequency analysis; Wigner-Ville Distribution; radar signal recognition; time-frequency analysis;
fLanguage
English
Publisher
ieee
Conference_Titel
Signal Processing Symposium (SPSympo), 2015
Conference_Location
Debe
Type
conf
DOI
10.1109/SPS.2015.7168292
Filename
7168292
Link To Document