{"title":"基于Wigner-Ville分布和RBF概率密度函数估计的雷达信号分类算法","authors":"Y. Grishin, K. Konopko","doi":"10.1109/IRS.2006.4338031","DOIUrl":null,"url":null,"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.","PeriodicalId":124475,"journal":{"name":"2006 International Radar Symposium","volume":"14 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2006-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A Classifying Algorithm for Radar Signals Using the Wigner-Ville Distribution and the RBF Probability Density Function Estimator\",\"authors\":\"Y. Grishin, K. Konopko\",\"doi\":\"10.1109/IRS.2006.4338031\",\"DOIUrl\":null,\"url\":null,\"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.\",\"PeriodicalId\":124475,\"journal\":{\"name\":\"2006 International Radar Symposium\",\"volume\":\"14 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2006-05-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2006 International Radar Symposium\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IRS.2006.4338031\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2006 International Radar Symposium","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IRS.2006.4338031","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A Classifying Algorithm for Radar Signals Using the Wigner-Ville Distribution and the RBF Probability Density Function Estimator
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.
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