{"title":"遥感系统中信号处理的自回归谱算法","authors":"V. I. Elfimov, V. K. Kochkina","doi":"10.1109/CRMICO.2014.6959839","DOIUrl":null,"url":null,"abstract":"Classical spectral methods of assessment are among the most sustainable methods. They apply to almost all classes of signals and noise, with fixed properties. The reason of application of the parametric models of random processes is due to the possibility of receipt on the basis of these models more accurate spectral estimates than it is possible by using the classical methods of spectral estimation.","PeriodicalId":6662,"journal":{"name":"2014 24th International Crimean Conference Microwave & Telecommunication Technology","volume":"129 1","pages":"1221-1222"},"PeriodicalIF":0.0000,"publicationDate":"2014-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Autoregressive spectral algorithms of signal processing in systems of remote sensing\",\"authors\":\"V. I. Elfimov, V. K. Kochkina\",\"doi\":\"10.1109/CRMICO.2014.6959839\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Classical spectral methods of assessment are among the most sustainable methods. They apply to almost all classes of signals and noise, with fixed properties. The reason of application of the parametric models of random processes is due to the possibility of receipt on the basis of these models more accurate spectral estimates than it is possible by using the classical methods of spectral estimation.\",\"PeriodicalId\":6662,\"journal\":{\"name\":\"2014 24th International Crimean Conference Microwave & Telecommunication Technology\",\"volume\":\"129 1\",\"pages\":\"1221-1222\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-11-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2014 24th International Crimean Conference Microwave & Telecommunication Technology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CRMICO.2014.6959839\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 24th International Crimean Conference Microwave & Telecommunication Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CRMICO.2014.6959839","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Autoregressive spectral algorithms of signal processing in systems of remote sensing
Classical spectral methods of assessment are among the most sustainable methods. They apply to almost all classes of signals and noise, with fixed properties. The reason of application of the parametric models of random processes is due to the possibility of receipt on the basis of these models more accurate spectral estimates than it is possible by using the classical methods of spectral estimation.