Iman Taghavi, M. Sabahi, F. Parvaresh, M. Mivehchy
{"title":"一种基于差分集码的压缩感知DOA估计方法","authors":"Iman Taghavi, M. Sabahi, F. Parvaresh, M. Mivehchy","doi":"10.1109/SPIS.2015.7422330","DOIUrl":null,"url":null,"abstract":"In this paper, we address the problem of direction-of-arrival (DOA) estimation using a novel spatial sampling scheme based on difference set (DS) codes, called DS-spatial sampling. It is shown that the proposed DS-spatial sampling scheme can be modeled by a deterministic dictionary with minimum coherence. We also develop a low complexity compressed sensing (CS) model for DOA estimation. The proposed methods can reduce the number of array elements as well as the number of receivers. Compared with the conventional DOA estimation algorithm, the proposed sampling and processing method can achieve significantly higher resolution.","PeriodicalId":424434,"journal":{"name":"2015 Signal Processing and Intelligent Systems Conference (SPIS)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A novel compressed sensing DOA estimation using difference set codes\",\"authors\":\"Iman Taghavi, M. Sabahi, F. Parvaresh, M. Mivehchy\",\"doi\":\"10.1109/SPIS.2015.7422330\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we address the problem of direction-of-arrival (DOA) estimation using a novel spatial sampling scheme based on difference set (DS) codes, called DS-spatial sampling. It is shown that the proposed DS-spatial sampling scheme can be modeled by a deterministic dictionary with minimum coherence. We also develop a low complexity compressed sensing (CS) model for DOA estimation. The proposed methods can reduce the number of array elements as well as the number of receivers. Compared with the conventional DOA estimation algorithm, the proposed sampling and processing method can achieve significantly higher resolution.\",\"PeriodicalId\":424434,\"journal\":{\"name\":\"2015 Signal Processing and Intelligent Systems Conference (SPIS)\",\"volume\":\"34 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2015 Signal Processing and Intelligent Systems Conference (SPIS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SPIS.2015.7422330\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 Signal Processing and Intelligent Systems Conference (SPIS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SPIS.2015.7422330","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A novel compressed sensing DOA estimation using difference set codes
In this paper, we address the problem of direction-of-arrival (DOA) estimation using a novel spatial sampling scheme based on difference set (DS) codes, called DS-spatial sampling. It is shown that the proposed DS-spatial sampling scheme can be modeled by a deterministic dictionary with minimum coherence. We also develop a low complexity compressed sensing (CS) model for DOA estimation. The proposed methods can reduce the number of array elements as well as the number of receivers. Compared with the conventional DOA estimation algorithm, the proposed sampling and processing method can achieve significantly higher resolution.