{"title":"基于MUSIC算法的l形阵列降维方位估计","authors":"Junliang Yang, Hu He, Shumin Wang","doi":"10.1145/3573942.3574113","DOIUrl":null,"url":null,"abstract":"According to the heavy computation and high cost of two-dimensional (2D) multiple signal classification (MUSIC) to achieve 2D direction of arrival (DOA) estimation in various complex arrays, this paper proposes a reduced-dimensional (RD) estimation algorithm based on L-shaped uniform array without the need of 2D spectral peak search and secondary optimization. This algorithm makes full use of the structural characteristics of L-shaped array, decomposes the L-shaped uniform array into two uniform linear arrays, and estimates the angle between the source and the X-axis and Y-axis by one-dimensional (1D) search respectively, then obtains the 2D-DOA estimation according to the geometric relationship and uses the maximum likelihood method for angle matching. In this algorithm, the time-consuming 2D search is transformed into 1D search, which greatly reduces the computational complexity. In order to further reduce the complexity and improve the estimation accuracy, the root-finding method can be used instead of one-dimensional search. The simulation results show that the proposed algorithm has higher DOA estimation performance as well as faster operation speed.","PeriodicalId":103293,"journal":{"name":"Proceedings of the 2022 5th International Conference on Artificial Intelligence and Pattern Recognition","volume":"12 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Reduced-Dimension DOA Estimation Based on MUSIC Algorithm in L-Shaped Array\",\"authors\":\"Junliang Yang, Hu He, Shumin Wang\",\"doi\":\"10.1145/3573942.3574113\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"According to the heavy computation and high cost of two-dimensional (2D) multiple signal classification (MUSIC) to achieve 2D direction of arrival (DOA) estimation in various complex arrays, this paper proposes a reduced-dimensional (RD) estimation algorithm based on L-shaped uniform array without the need of 2D spectral peak search and secondary optimization. This algorithm makes full use of the structural characteristics of L-shaped array, decomposes the L-shaped uniform array into two uniform linear arrays, and estimates the angle between the source and the X-axis and Y-axis by one-dimensional (1D) search respectively, then obtains the 2D-DOA estimation according to the geometric relationship and uses the maximum likelihood method for angle matching. In this algorithm, the time-consuming 2D search is transformed into 1D search, which greatly reduces the computational complexity. In order to further reduce the complexity and improve the estimation accuracy, the root-finding method can be used instead of one-dimensional search. The simulation results show that the proposed algorithm has higher DOA estimation performance as well as faster operation speed.\",\"PeriodicalId\":103293,\"journal\":{\"name\":\"Proceedings of the 2022 5th International Conference on Artificial Intelligence and Pattern Recognition\",\"volume\":\"12 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/10.1145/3573942.3574113\",\"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/10.1145/3573942.3574113","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Reduced-Dimension DOA Estimation Based on MUSIC Algorithm in L-Shaped Array
According to the heavy computation and high cost of two-dimensional (2D) multiple signal classification (MUSIC) to achieve 2D direction of arrival (DOA) estimation in various complex arrays, this paper proposes a reduced-dimensional (RD) estimation algorithm based on L-shaped uniform array without the need of 2D spectral peak search and secondary optimization. This algorithm makes full use of the structural characteristics of L-shaped array, decomposes the L-shaped uniform array into two uniform linear arrays, and estimates the angle between the source and the X-axis and Y-axis by one-dimensional (1D) search respectively, then obtains the 2D-DOA estimation according to the geometric relationship and uses the maximum likelihood method for angle matching. In this algorithm, the time-consuming 2D search is transformed into 1D search, which greatly reduces the computational complexity. In order to further reduce the complexity and improve the estimation accuracy, the root-finding method can be used instead of one-dimensional search. The simulation results show that the proposed algorithm has higher DOA estimation performance as well as faster operation speed.