{"title":"基于四阶累积量的阵列流形匹配算法用于两个并行嵌套阵列的二维DOA估计","authors":"Sheng Liu, Jing Zhao, Yu Zhang","doi":"10.1504/IJCSE.2021.115091","DOIUrl":null,"url":null,"abstract":"In this paper, a two-dimensional (2D) direction-of-arrival (DOA) estimation algorithm with two parallel nested arrays is developed. Firstly, a constructor method for fourth-order cumulant (FOC) matrices is given according to the distribution of sensors. Then a pre-existing DOA estimation technique is firstly used to estimate the elevation angles and an improved unilateral array manifold matching (AMM) algorithm is used to estimate the azimuth angles. Compared with some classical 2D DOA estimation algorithms, the proposed algorithm has much better estimation performance, particularly in the case of low SNR environment. Compared with some traditional FOC-based algorithms, the proposed algorithm has higher estimation precision. Simulation results can illustrate the validity of proposed algorithm.","PeriodicalId":340410,"journal":{"name":"Int. J. Comput. Sci. Eng.","volume":"161 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Array manifold matching algorithm based on fourth-order cumulant for 2D DOA estimation with two parallel nested arrays\",\"authors\":\"Sheng Liu, Jing Zhao, Yu Zhang\",\"doi\":\"10.1504/IJCSE.2021.115091\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, a two-dimensional (2D) direction-of-arrival (DOA) estimation algorithm with two parallel nested arrays is developed. Firstly, a constructor method for fourth-order cumulant (FOC) matrices is given according to the distribution of sensors. Then a pre-existing DOA estimation technique is firstly used to estimate the elevation angles and an improved unilateral array manifold matching (AMM) algorithm is used to estimate the azimuth angles. Compared with some classical 2D DOA estimation algorithms, the proposed algorithm has much better estimation performance, particularly in the case of low SNR environment. Compared with some traditional FOC-based algorithms, the proposed algorithm has higher estimation precision. Simulation results can illustrate the validity of proposed algorithm.\",\"PeriodicalId\":340410,\"journal\":{\"name\":\"Int. J. Comput. Sci. Eng.\",\"volume\":\"161 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-05-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Int. J. Comput. Sci. Eng.\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1504/IJCSE.2021.115091\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Int. J. Comput. Sci. Eng.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1504/IJCSE.2021.115091","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Array manifold matching algorithm based on fourth-order cumulant for 2D DOA estimation with two parallel nested arrays
In this paper, a two-dimensional (2D) direction-of-arrival (DOA) estimation algorithm with two parallel nested arrays is developed. Firstly, a constructor method for fourth-order cumulant (FOC) matrices is given according to the distribution of sensors. Then a pre-existing DOA estimation technique is firstly used to estimate the elevation angles and an improved unilateral array manifold matching (AMM) algorithm is used to estimate the azimuth angles. Compared with some classical 2D DOA estimation algorithms, the proposed algorithm has much better estimation performance, particularly in the case of low SNR environment. Compared with some traditional FOC-based algorithms, the proposed algorithm has higher estimation precision. Simulation results can illustrate the validity of proposed algorithm.