{"title":"一种无源数估计的任意几何非平面阵列高分辨率算法","authors":"H. Ke, Z. Xiaomin, Han Peng, Zhao Yan-an, Yu Yang","doi":"10.1109/ICSAP.2010.25","DOIUrl":null,"url":null,"abstract":"The performances of most of the high resolution methods always depend on the estimation of the source number. In real application, when the estimated number of signals is not correct, the orthogonality between signal subspace and noise subspace can not be maintained any more. And the performance of DOA estimation algorithm will deteriorate severely. In this paper, a high resolution algorithm called m-MVM without source number estimation and Eigen decomposition for Direction-Of-Arrival (DOA) estimation is proposed, which is an improvement of the Minimum Variance Method (MVM). Furthermore, it is suitable to nonplanar arrays of arbitrary geometries. Some representative computer simulations are presented to illustrate the performance comparison between different algorithms and different arrays.","PeriodicalId":303366,"journal":{"name":"2010 International Conference on Signal Acquisition and Processing","volume":"7 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"A High Resolution Algorithm for Nonplanar Array with Arbitrary Geometry without Source Number Estimation\",\"authors\":\"H. Ke, Z. Xiaomin, Han Peng, Zhao Yan-an, Yu Yang\",\"doi\":\"10.1109/ICSAP.2010.25\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The performances of most of the high resolution methods always depend on the estimation of the source number. In real application, when the estimated number of signals is not correct, the orthogonality between signal subspace and noise subspace can not be maintained any more. And the performance of DOA estimation algorithm will deteriorate severely. In this paper, a high resolution algorithm called m-MVM without source number estimation and Eigen decomposition for Direction-Of-Arrival (DOA) estimation is proposed, which is an improvement of the Minimum Variance Method (MVM). Furthermore, it is suitable to nonplanar arrays of arbitrary geometries. Some representative computer simulations are presented to illustrate the performance comparison between different algorithms and different arrays.\",\"PeriodicalId\":303366,\"journal\":{\"name\":\"2010 International Conference on Signal Acquisition and Processing\",\"volume\":\"7 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-02-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2010 International Conference on Signal Acquisition and Processing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICSAP.2010.25\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 International Conference on Signal Acquisition and Processing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICSAP.2010.25","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A High Resolution Algorithm for Nonplanar Array with Arbitrary Geometry without Source Number Estimation
The performances of most of the high resolution methods always depend on the estimation of the source number. In real application, when the estimated number of signals is not correct, the orthogonality between signal subspace and noise subspace can not be maintained any more. And the performance of DOA estimation algorithm will deteriorate severely. In this paper, a high resolution algorithm called m-MVM without source number estimation and Eigen decomposition for Direction-Of-Arrival (DOA) estimation is proposed, which is an improvement of the Minimum Variance Method (MVM). Furthermore, it is suitable to nonplanar arrays of arbitrary geometries. Some representative computer simulations are presented to illustrate the performance comparison between different algorithms and different arrays.