{"title":"基于嵌套数组的复杂wishart分布的待定源数估计","authors":"Yu Rong, D. Bliss","doi":"10.1109/MILCOM.2017.8170830","DOIUrl":null,"url":null,"abstract":"We propose a likelihood test for a covariance estimated from sample data which is used to determine the number of narrow band source signals. This Minimum Description Length (MDL) estimator is shown to be robust against deviations from the assumption of equal noise level across the array. A number of source Direction-Of-Arrivals (DOA) greater than the number of physical array elements is of interest. We propose a novel spatial smoothing algorithm which accurately estimates parameters for the covariance likelihood test. Improved parameter estimation performance is achieved when compared with the conventional spatial smoothing algorithm. Finally, the proposed source number estimator is validated through numerical results and compared with other recently developed approaches.","PeriodicalId":113767,"journal":{"name":"MILCOM 2017 - 2017 IEEE Military Communications Conference (MILCOM)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Underdetermined source number estimation based on complex wishart distribution using nested arrays\",\"authors\":\"Yu Rong, D. Bliss\",\"doi\":\"10.1109/MILCOM.2017.8170830\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We propose a likelihood test for a covariance estimated from sample data which is used to determine the number of narrow band source signals. This Minimum Description Length (MDL) estimator is shown to be robust against deviations from the assumption of equal noise level across the array. A number of source Direction-Of-Arrivals (DOA) greater than the number of physical array elements is of interest. We propose a novel spatial smoothing algorithm which accurately estimates parameters for the covariance likelihood test. Improved parameter estimation performance is achieved when compared with the conventional spatial smoothing algorithm. Finally, the proposed source number estimator is validated through numerical results and compared with other recently developed approaches.\",\"PeriodicalId\":113767,\"journal\":{\"name\":\"MILCOM 2017 - 2017 IEEE Military Communications Conference (MILCOM)\",\"volume\":\"27 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"MILCOM 2017 - 2017 IEEE Military Communications Conference (MILCOM)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/MILCOM.2017.8170830\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"MILCOM 2017 - 2017 IEEE Military Communications Conference (MILCOM)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/MILCOM.2017.8170830","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Underdetermined source number estimation based on complex wishart distribution using nested arrays
We propose a likelihood test for a covariance estimated from sample data which is used to determine the number of narrow band source signals. This Minimum Description Length (MDL) estimator is shown to be robust against deviations from the assumption of equal noise level across the array. A number of source Direction-Of-Arrivals (DOA) greater than the number of physical array elements is of interest. We propose a novel spatial smoothing algorithm which accurately estimates parameters for the covariance likelihood test. Improved parameter estimation performance is achieved when compared with the conventional spatial smoothing algorithm. Finally, the proposed source number estimator is validated through numerical results and compared with other recently developed approaches.