{"title":"Radar signal recognition based on time-frequency representations and multidimensional probability density function estimator","authors":"K. Konopko, Y. Grishin, D. Janczak","doi":"10.1109/SPS.2015.7168292","DOIUrl":null,"url":null,"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.","PeriodicalId":193902,"journal":{"name":"2015 Signal Processing Symposium (SPSympo)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"16","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 Signal Processing Symposium (SPSympo)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SPS.2015.7168292","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 16
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.
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