{"title":"各种目标雷达回波数据库，并进行频谱分析","authors":"M. Andric, Boban P. Bondzulic, B. Zrnic","doi":"10.1109/NEUREL.2010.5644074","DOIUrl":null,"url":null,"abstract":"In this paper we describe a database, noted as RadEch Database, containing radar echoes from various targets. The data has been collected in controlled test environments at the premises of Military Academy — Republic of Serbia. Our goal is to provide a balanced and comprehensive database to enable reproducible research results in the field of classification of ground moving targets (pattern recognition). A time-frequency analysis of radar echoes has been performed, in order to identify the main features of the various targets. The RadEch Database is freely available for download and we hope that our database provides researchers with a valuable tool to benchmark and improve the performance of classification algorithms.","PeriodicalId":227890,"journal":{"name":"10th Symposium on Neural Network Applications in Electrical Engineering","volume":"2011 9","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"32","resultStr":"{\"title\":\"The database of radar echoes from various targets with spectral analysis\",\"authors\":\"M. Andric, Boban P. Bondzulic, B. Zrnic\",\"doi\":\"10.1109/NEUREL.2010.5644074\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper we describe a database, noted as RadEch Database, containing radar echoes from various targets. The data has been collected in controlled test environments at the premises of Military Academy — Republic of Serbia. Our goal is to provide a balanced and comprehensive database to enable reproducible research results in the field of classification of ground moving targets (pattern recognition). A time-frequency analysis of radar echoes has been performed, in order to identify the main features of the various targets. The RadEch Database is freely available for download and we hope that our database provides researchers with a valuable tool to benchmark and improve the performance of classification algorithms.\",\"PeriodicalId\":227890,\"journal\":{\"name\":\"10th Symposium on Neural Network Applications in Electrical Engineering\",\"volume\":\"2011 9\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-11-29\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"32\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"10th Symposium on Neural Network Applications in Electrical Engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/NEUREL.2010.5644074\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"10th Symposium on Neural Network Applications in Electrical Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/NEUREL.2010.5644074","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
The database of radar echoes from various targets with spectral analysis
In this paper we describe a database, noted as RadEch Database, containing radar echoes from various targets. The data has been collected in controlled test environments at the premises of Military Academy — Republic of Serbia. Our goal is to provide a balanced and comprehensive database to enable reproducible research results in the field of classification of ground moving targets (pattern recognition). A time-frequency analysis of radar echoes has been performed, in order to identify the main features of the various targets. The RadEch Database is freely available for download and we hope that our database provides researchers with a valuable tool to benchmark and improve the performance of classification algorithms.
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