Yi Li;Weijie Xia;Lingzhi Zhu;Cao Qu;Jianjiang Zhou
{"title":"相干分布式毫米波雷达的高分辨率DOA估计","authors":"Yi Li;Weijie Xia;Lingzhi Zhu;Cao Qu;Jianjiang Zhou","doi":"10.1109/TAES.2024.3525444","DOIUrl":null,"url":null,"abstract":"Achieving high angular resolution estimation is essential for enhancing environmental perception and accurately detecting extended targets. However, implementing a large aperture radar system as a single sensor faces significant technical and economic challenges. Radar networks, comprising multiple individual radar sensors, offer a promising solution to these obstacles. In this article, we propose a method for high resolution direction-of-arrival (DOA) estimation tailored for coherent distributed millimeter-wave radar systems. Our approach leverages multiple-input multiple-output technology and distributed arrays to construct a virtual sparse array capable of synthesizing a full uniform array covariance matrix through specific correlation transformation. Furthermore, we introduce a joint optimization method for directly angle finding that efficiently addresses large-scale optimization problems by exploiting both sparsity and low-rank properties, thereby circumventing the traditional sequential steps of matrix reconstruction and DOA estimation. We employ the alternating direction method of multipliers to ensure reliable convergence. Our proposed model and method have been extensively validated through comprehensive simulations, highlighting their advantages within the realm of distributed radar systems.","PeriodicalId":13157,"journal":{"name":"IEEE Transactions on Aerospace and Electronic Systems","volume":"61 3","pages":"6098-6109"},"PeriodicalIF":5.7000,"publicationDate":"2025-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"High Resolution DOA Estimation of Coherent Distributed Millimeter-Wave Radar\",\"authors\":\"Yi Li;Weijie Xia;Lingzhi Zhu;Cao Qu;Jianjiang Zhou\",\"doi\":\"10.1109/TAES.2024.3525444\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Achieving high angular resolution estimation is essential for enhancing environmental perception and accurately detecting extended targets. However, implementing a large aperture radar system as a single sensor faces significant technical and economic challenges. Radar networks, comprising multiple individual radar sensors, offer a promising solution to these obstacles. In this article, we propose a method for high resolution direction-of-arrival (DOA) estimation tailored for coherent distributed millimeter-wave radar systems. Our approach leverages multiple-input multiple-output technology and distributed arrays to construct a virtual sparse array capable of synthesizing a full uniform array covariance matrix through specific correlation transformation. Furthermore, we introduce a joint optimization method for directly angle finding that efficiently addresses large-scale optimization problems by exploiting both sparsity and low-rank properties, thereby circumventing the traditional sequential steps of matrix reconstruction and DOA estimation. We employ the alternating direction method of multipliers to ensure reliable convergence. Our proposed model and method have been extensively validated through comprehensive simulations, highlighting their advantages within the realm of distributed radar systems.\",\"PeriodicalId\":13157,\"journal\":{\"name\":\"IEEE Transactions on Aerospace and Electronic Systems\",\"volume\":\"61 3\",\"pages\":\"6098-6109\"},\"PeriodicalIF\":5.7000,\"publicationDate\":\"2025-01-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE Transactions on Aerospace and Electronic Systems\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://ieeexplore.ieee.org/document/10847921/\",\"RegionNum\":2,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ENGINEERING, AEROSPACE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Transactions on Aerospace and Electronic Systems","FirstCategoryId":"94","ListUrlMain":"https://ieeexplore.ieee.org/document/10847921/","RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, AEROSPACE","Score":null,"Total":0}
High Resolution DOA Estimation of Coherent Distributed Millimeter-Wave Radar
Achieving high angular resolution estimation is essential for enhancing environmental perception and accurately detecting extended targets. However, implementing a large aperture radar system as a single sensor faces significant technical and economic challenges. Radar networks, comprising multiple individual radar sensors, offer a promising solution to these obstacles. In this article, we propose a method for high resolution direction-of-arrival (DOA) estimation tailored for coherent distributed millimeter-wave radar systems. Our approach leverages multiple-input multiple-output technology and distributed arrays to construct a virtual sparse array capable of synthesizing a full uniform array covariance matrix through specific correlation transformation. Furthermore, we introduce a joint optimization method for directly angle finding that efficiently addresses large-scale optimization problems by exploiting both sparsity and low-rank properties, thereby circumventing the traditional sequential steps of matrix reconstruction and DOA estimation. We employ the alternating direction method of multipliers to ensure reliable convergence. Our proposed model and method have been extensively validated through comprehensive simulations, highlighting their advantages within the realm of distributed radar systems.
期刊介绍:
IEEE Transactions on Aerospace and Electronic Systems focuses on the organization, design, development, integration, and operation of complex systems for space, air, ocean, or ground environment. These systems include, but are not limited to, navigation, avionics, spacecraft, aerospace power, radar, sonar, telemetry, defense, transportation, automated testing, and command and control.