Hua Chen, Yonghong Liu, Qing Wang, Wei Liu, Zongju Peng, Gang Wang
{"title":"A general ESPRIT method for noncircularity-based incoherently distributed sources","authors":"Hua Chen, Yonghong Liu, Qing Wang, Wei Liu, Zongju Peng, Gang Wang","doi":"10.1109/SAM48682.2020.9104310","DOIUrl":null,"url":null,"abstract":"In this paper, a reduced-rank direction-of-arrival (DOA) estimation algorithm for incoherently distributed (ID) noncircular sources based on a uniform linear array (ULA) is proposed. First the noncircularity property of the signal is utilized to establish an extended generalized array manifold (GAM) model based on the first-order Taylor series approximation. Then, the central DOA of source signals is obtained based on the generalized shift invariance property of the array manifold and the reduced-rank principle. Compared with the algorithm without exploiting the noncircularity information, the proposed algorithm can achieve a higher accuracy and handle more sources. Simulation results are provided to demonstrate the performance of the proposed algorithm.","PeriodicalId":6753,"journal":{"name":"2020 IEEE 11th Sensor Array and Multichannel Signal Processing Workshop (SAM)","volume":"2 1","pages":"1-4"},"PeriodicalIF":0.0000,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 IEEE 11th Sensor Array and Multichannel Signal Processing Workshop (SAM)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SAM48682.2020.9104310","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
In this paper, a reduced-rank direction-of-arrival (DOA) estimation algorithm for incoherently distributed (ID) noncircular sources based on a uniform linear array (ULA) is proposed. First the noncircularity property of the signal is utilized to establish an extended generalized array manifold (GAM) model based on the first-order Taylor series approximation. Then, the central DOA of source signals is obtained based on the generalized shift invariance property of the array manifold and the reduced-rank principle. Compared with the algorithm without exploiting the noncircularity information, the proposed algorithm can achieve a higher accuracy and handle more sources. Simulation results are provided to demonstrate the performance of the proposed algorithm.