{"title":"基于协方差矩阵重构的移位协素阵列DOA估计","authors":"Wei Yang, Dongming Xu, Jiaqi Xue","doi":"10.1145/3573942.3574112","DOIUrl":null,"url":null,"abstract":"Aiming at the problem that the maximum number of continuous uniform array elements of the virtual array extended by the coprime array algorithm is small and the degree of freedom is still low. A matrix reconstruction DOA estimation algorithm based on virtual array interpolation is proposed. Firstly, the general coprime array is improved by optimizing the array layout to form a new array, and the new array is derived from a non-uniform virtual array, which increases the number of array elements and improves the degree of freedom; secondly, the idea of virtual array interpolation is used to fill the holes in the virtual domain A uniform linear virtual array is constructed, and finally the DOA is estimated by optimizing the design through atomic norm minimization and sparse reconstruction of the covariance matrix. The algorithm improves the degree of freedom of the array and makes full use of the information in the virtual array. The simulation results show the effectiveness of the new array algorithm.","PeriodicalId":103293,"journal":{"name":"Proceedings of the 2022 5th International Conference on Artificial Intelligence and Pattern Recognition","volume":"13 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"DOA Estimation of Shifted Coprime Array Based on Covariance Matrix Reconstruction\",\"authors\":\"Wei Yang, Dongming Xu, Jiaqi Xue\",\"doi\":\"10.1145/3573942.3574112\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Aiming at the problem that the maximum number of continuous uniform array elements of the virtual array extended by the coprime array algorithm is small and the degree of freedom is still low. A matrix reconstruction DOA estimation algorithm based on virtual array interpolation is proposed. Firstly, the general coprime array is improved by optimizing the array layout to form a new array, and the new array is derived from a non-uniform virtual array, which increases the number of array elements and improves the degree of freedom; secondly, the idea of virtual array interpolation is used to fill the holes in the virtual domain A uniform linear virtual array is constructed, and finally the DOA is estimated by optimizing the design through atomic norm minimization and sparse reconstruction of the covariance matrix. The algorithm improves the degree of freedom of the array and makes full use of the information in the virtual array. The simulation results show the effectiveness of the new array algorithm.\",\"PeriodicalId\":103293,\"journal\":{\"name\":\"Proceedings of the 2022 5th International Conference on Artificial Intelligence and Pattern Recognition\",\"volume\":\"13 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-09-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 2022 5th International Conference on Artificial Intelligence and Pattern Recognition\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3573942.3574112\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 2022 5th International Conference on Artificial Intelligence and Pattern Recognition","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3573942.3574112","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
DOA Estimation of Shifted Coprime Array Based on Covariance Matrix Reconstruction
Aiming at the problem that the maximum number of continuous uniform array elements of the virtual array extended by the coprime array algorithm is small and the degree of freedom is still low. A matrix reconstruction DOA estimation algorithm based on virtual array interpolation is proposed. Firstly, the general coprime array is improved by optimizing the array layout to form a new array, and the new array is derived from a non-uniform virtual array, which increases the number of array elements and improves the degree of freedom; secondly, the idea of virtual array interpolation is used to fill the holes in the virtual domain A uniform linear virtual array is constructed, and finally the DOA is estimated by optimizing the design through atomic norm minimization and sparse reconstruction of the covariance matrix. The algorithm improves the degree of freedom of the array and makes full use of the information in the virtual array. The simulation results show the effectiveness of the new array algorithm.