{"title":"基于硬件约束的压缩感知到达方向估计的自适应感知矩阵设计","authors":"Berkan Kiliç, M. Kalfa, O. Arikan","doi":"10.23919/USNC/URSI49741.2020.9321646","DOIUrl":null,"url":null,"abstract":"Compressive sensing (CS) techniques are able to decrease hardware complexity in various applications including direction of arrival (DoA) estimation using antenna arrays. In CS based DoA estimation systems, analog outputs of the antenna elements are compressed by a matrix called sensing matrix and digitized after compression. This operation reduces the number of analog-to-digital converters in the hardware implementation. However, constraints resulting from hardware implementation of sensing matrices are not considered in general which can drastically increase the system complexity. In this study, we propose a novel adaptive sensing matrix design methodology by including such hardware implementation constraints.","PeriodicalId":443426,"journal":{"name":"2020 IEEE USNC-CNC-URSI North American Radio Science Meeting (Joint with AP-S Symposium)","volume":"45 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Adaptive Sensing Matrix Design in Compressive Sensing Based Direction of Arrival Estimation with Hardware Constraints\",\"authors\":\"Berkan Kiliç, M. Kalfa, O. Arikan\",\"doi\":\"10.23919/USNC/URSI49741.2020.9321646\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Compressive sensing (CS) techniques are able to decrease hardware complexity in various applications including direction of arrival (DoA) estimation using antenna arrays. In CS based DoA estimation systems, analog outputs of the antenna elements are compressed by a matrix called sensing matrix and digitized after compression. This operation reduces the number of analog-to-digital converters in the hardware implementation. However, constraints resulting from hardware implementation of sensing matrices are not considered in general which can drastically increase the system complexity. In this study, we propose a novel adaptive sensing matrix design methodology by including such hardware implementation constraints.\",\"PeriodicalId\":443426,\"journal\":{\"name\":\"2020 IEEE USNC-CNC-URSI North American Radio Science Meeting (Joint with AP-S Symposium)\",\"volume\":\"45 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-07-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 IEEE USNC-CNC-URSI North American Radio Science Meeting (Joint with AP-S Symposium)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.23919/USNC/URSI49741.2020.9321646\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 IEEE USNC-CNC-URSI North American Radio Science Meeting (Joint with AP-S Symposium)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.23919/USNC/URSI49741.2020.9321646","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Adaptive Sensing Matrix Design in Compressive Sensing Based Direction of Arrival Estimation with Hardware Constraints
Compressive sensing (CS) techniques are able to decrease hardware complexity in various applications including direction of arrival (DoA) estimation using antenna arrays. In CS based DoA estimation systems, analog outputs of the antenna elements are compressed by a matrix called sensing matrix and digitized after compression. This operation reduces the number of analog-to-digital converters in the hardware implementation. However, constraints resulting from hardware implementation of sensing matrices are not considered in general which can drastically increase the system complexity. In this study, we propose a novel adaptive sensing matrix design methodology by including such hardware implementation constraints.