Volume 12 Issue 5
Oct.  2023
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Article Navigation >  Journal of Radars  > 2023  >  12(5): 986-999
SONG Jiaqi and TAO Haihong. A fast parameter estimation algorithm for near-field non-circular signals[J]. Journal of Radars, 2020, 9(4): 632–639. doi: 10.12000/JR20053
Citation: SHU Yue, FU Dongning, CHEN Zhanye, et al. Super-resolution DOA estimation method for a moving target equipped with a millimeter-wave radar based on RD-ANM[J]. Journal of Radars, 2023, 12(5): 986–999. doi: 10.12000/JR23040
shu

Super-resolution DOA Estimation Method for a Moving Target Equipped with a Millimeter-wave Radar Based on RD-ANM

DOI: 10.12000/JR23040
  • 1.

    School of Microelectronics and Communication Engineering, Chongqing University, Chongqing 400044, China

  • 2.

    Hwa Create Technology Cop., Ltd., Beijing 100193, China

  • 3.

    HWA-NCUT Radar RF Simulation Laboratory, Beijing 100144, China

  • 4.

    State Key Laboratory of Millimeter Waves, School of Information Science and Engineering, Southeast University, Nanjing 210096, China

  • 5.

    Key Laboratory of Underwater Acoustic Signal Processing of Ministry of Education, School of Information Science and Engineering, Southeast University, Nanjing 210096, China

Funds:  The National Natural Science Foundation of China (62001062, 62271142, 61901112)
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    Abstract
  • Super-resolution Direction of Arrival (DOA) estimation is a critical problem related to vehicle-borne Millimeter-wave radars that needs to be solved to realize accurate target positioning and tracking. Based on the common conditions of limited array aperture, low snapshot, low signal-to-noise ratio, and coherent sources with respect to vehicle-borne scenarios, a super-resolution DOA estimation method for a moving target with an MMW radar based on Range-Doppler Atom Norm Minimize (RD-ANM) is proposed herein. First, an array for receiving signals in the range-Doppler domain is constructed based on the radar echo of the moving target. Then, the compensation vector for the Doppler coupling phase of the moving target is designed to reduce the influence of target motion on DOA estimation. Finally, a multitarget super-resolution DOA estimation method based on the atomic norm framework is proposed herein. Compared to the existing DOA estimation algorithm, the proposed algorithm can achieve higher angular resolution and estimation accuracy owing to low signal-to-noise ratio and single snapshot processing conditions, as well as robust performance in processing coherent sources without sacrificing array aperture. The effectiveness of the proposed algorithm is proven via theoretical analyses, numerical simulations, and experiments.

     

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    • References(24)
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    Created with Highcharts 5.0.7Chart context menuAccess Area Distribution其他: 4.4 %其他: 4.4 %其他: 0.4 %其他: 0.4 %Central District: 0.0 %Central District: 0.0 %China: 0.5 %China: 0.5 %Falls Church: 0.0 %Falls Church: 0.0 %India: 0.0 %India: 0.0 %Jonquiere: 0.1 %Jonquiere: 0.1 %Rochester: 0.0 %Rochester: 0.0 %Taiwan, China: 0.1 %Taiwan, China: 0.1 %Tiruchi: 0.1 %Tiruchi: 0.1 %United States: 0.0 %United States: 0.0 %[]: 0.7 %[]: 0.7 %三亚: 0.1 %三亚: 0.1 %上海: 1.1 %上海: 1.1 %东莞: 0.1 %东莞: 0.1 %临汾: 0.0 %临汾: 0.0 %临沂: 0.3 %临沂: 0.3 %丹东: 0.0 %丹东: 0.0 %丽江: 0.0 %丽江: 0.0 %亳州: 0.1 %亳州: 0.1 %佛山: 0.1 %佛山: 0.1 %保定: 0.1 %保定: 0.1 %信阳: 0.0 %信阳: 0.0 %六安: 0.0 %六安: 0.0 %兰州: 0.0 %兰州: 0.0 %兰辛: 0.0 %兰辛: 0.0 %内蒙古自治区包头: 0.1 %内蒙古自治区包头: 0.1 %加利福尼亚: 0.1 %加利福尼亚: 0.1 %包头: 0.0 %包头: 0.0 %北京: 15.6 %北京: 15.6 %北京市: 0.2 %北京市: 0.2 %北海: 0.1 %北海: 0.1 %十堰: 0.0 %十堰: 0.0 %南京: 1.3 %南京: 1.3 %南京市: 0.0 %南京市: 0.0 %南充: 0.0 %南充: 0.0 %南宁: 0.1 %南宁: 0.1 %南昌: 0.1 %南昌: 0.1 %南通: 0.1 %南通: 0.1 %南阳: 0.1 %南阳: 0.1 %厦门: 0.2 %厦门: 0.2 %台北: 0.1 %台北: 0.1 %台州: 0.1 %台州: 0.1 %台湾省: 0.0 %台湾省: 0.0 %合肥: 0.2 %合肥: 0.2 %合肥市: 0.0 %合肥市: 0.0 %呼和浩特: 0.3 %呼和浩特: 0.3 %咸阳: 0.1 %咸阳: 0.1 %哈尔滨: 0.3 %哈尔滨: 0.3 %哈尔滨市: 0.0 %哈尔滨市: 0.0 %哥伦布: 0.0 %哥伦布: 0.0 %嘉兴: 0.0 %嘉兴: 0.0 %四平: 0.2 %四平: 0.2 %大同: 0.1 %大同: 0.1 %大连: 0.2 %大连: 0.2 %天津: 0.4 %天津: 0.4 %威海: 0.0 %威海: 0.0 %孟买: 0.2 %孟买: 0.2 %宁夏回族自治区中卫: 0.0 %宁夏回族自治区中卫: 0.0 %宁波: 0.0 %宁波: 0.0 %安康: 0.1 %安康: 0.1 %宜春: 0.0 %宜春: 0.0 %宝鸡: 0.0 %宝鸡: 0.0 %宣城: 0.1 %宣城: 0.1 %宿迁: 0.1 %宿迁: 0.1 %巴彦淖尔: 0.0 %巴彦淖尔: 0.0 %常州: 0.1 %常州: 0.1 %平顶山: 0.1 %平顶山: 0.1 %广州: 0.9 %广州: 0.9 %庆阳: 0.0 %庆阳: 0.0 %库比蒂诺: 0.1 %库比蒂诺: 0.1 %延安: 0.0 %延安: 0.0 %开封: 0.1 %开封: 0.1 %张家口: 0.9 %张家口: 0.9 %张家界: 0.0 %张家界: 0.0 %德罕: 0.2 %德罕: 0.2 %德里: 0.1 %德里: 0.1 %成都: 0.4 %成都: 0.4 %成都市: 0.0 %成都市: 0.0 %扬州: 0.1 %扬州: 0.1 %新乡: 0.5 %新乡: 0.5 %无锡: 0.1 %无锡: 0.1 %昆明: 0.2 %昆明: 0.2 %昌吉: 0.0 %昌吉: 0.0 %晋城: 0.0 %晋城: 0.0 %普洱: 0.1 %普洱: 0.1 %杭州: 0.9 %杭州: 0.9 %枣庄: 0.1 %枣庄: 0.1 %株洲: 0.2 %株洲: 0.2 %格兰特县: 0.1 %格兰特县: 0.1 %榆林: 0.0 %榆林: 0.0 %武汉: 0.5 %武汉: 0.5 %沈阳: 0.2 %沈阳: 0.2 %泰米尔纳德: 0.1 %泰米尔纳德: 0.1 %洛阳: 0.1 %洛阳: 0.1 %济南: 0.2 %济南: 0.2 %济宁: 0.0 %济宁: 0.0 %海口: 0.0 %海口: 0.0 %淮南: 0.0 %淮南: 0.0 %淮安: 0.0 %淮安: 0.0 %深圳: 0.7 %深圳: 0.7 %温州: 0.1 %温州: 0.1 %渭南: 0.0 %渭南: 0.0 %湖州: 0.2 %湖州: 0.2 %湘潭: 0.0 %湘潭: 0.0 %滨州: 0.0 %滨州: 0.0 %漯河: 0.3 %漯河: 0.3 %潍坊: 0.1 %潍坊: 0.1 %潍坊市寿光: 0.1 %潍坊市寿光: 0.1 %烟台: 0.2 %烟台: 0.2 %玉林: 0.1 %玉林: 0.1 %珠海: 4.0 %珠海: 4.0 %白银: 0.0 %白银: 0.0 %益阳: 0.0 %益阳: 0.0 %石家庄: 0.2 %石家庄: 0.2 %石家庄市: 0.0 %石家庄市: 0.0 %秦皇岛: 0.1 %秦皇岛: 0.1 %纽约: 0.2 %纽约: 0.2 %绵阳: 0.1 %绵阳: 0.1 %美国伊利诺斯芝加哥: 0.0 %美国伊利诺斯芝加哥: 0.0 %舟山: 0.0 %舟山: 0.0 %芒廷维尤: 16.0 %芒廷维尤: 16.0 %芜湖: 0.0 %芜湖: 0.0 %芝加哥: 0.4 %芝加哥: 0.4 %苏州: 0.3 %苏州: 0.3 %莆田: 0.1 %莆田: 0.1 %莫斯科: 0.0 %莫斯科: 0.0 %菏泽: 0.0 %菏泽: 0.0 %营口: 0.1 %营口: 0.1 %衡水: 0.1 %衡水: 0.1 %衡阳: 0.1 %衡阳: 0.1 %衢州: 0.1 %衢州: 0.1 %西宁: 35.0 %西宁: 35.0 %西安: 1.0 %西安: 1.0 %诺沃克: 0.0 %诺沃克: 0.0 %贵港: 0.3 %贵港: 0.3 %贵阳: 0.1 %贵阳: 0.1 %赤峰: 0.1 %赤峰: 0.1 %运城: 0.4 %运城: 0.4 %连云港: 0.1 %连云港: 0.1 %邢台: 0.1 %邢台: 0.1 %邯郸: 0.1 %邯郸: 0.1 %郑州: 1.4 %郑州: 1.4 %郴州: 0.0 %郴州: 0.0 %重庆: 0.2 %重庆: 0.2 %重庆市: 0.0 %重庆市: 0.0 %钱德勒: 0.1 %钱德勒: 0.1 %长春: 0.2 %长春: 0.2 %长沙: 0.8 %长沙: 0.8 %长治: 0.1 %长治: 0.1 %阳泉: 0.0 %阳泉: 0.0 %雅加达: 0.1 %雅加达: 0.1 %青岛: 1.5 %青岛: 1.5 %香港特别行政区: 0.0 %香港特别行政区: 0.0 %齐齐哈尔: 0.0 %齐齐哈尔: 0.0 %其他其他Central DistrictChinaFalls ChurchIndiaJonquiereRochesterTaiwan, ChinaTiruchiUnited States[]三亚上海东莞临汾临沂丹东丽江亳州佛山保定信阳六安兰州兰辛内蒙古自治区包头加利福尼亚包头北京北京市北海十堰南京南京市南充南宁南昌南通南阳厦门台北台州台湾省合肥合肥市呼和浩特咸阳哈尔滨哈尔滨市哥伦布嘉兴四平大同大连天津威海孟买宁夏回族自治区中卫宁波安康宜春宝鸡宣城宿迁巴彦淖尔常州平顶山广州庆阳库比蒂诺延安开封张家口张家界德罕德里成都成都市扬州新乡无锡昆明昌吉晋城普洱杭州枣庄株洲格兰特县榆林武汉沈阳泰米尔纳德洛阳济南济宁海口淮南淮安深圳温州渭南湖州湘潭滨州漯河潍坊潍坊市寿光烟台玉林珠海白银益阳石家庄石家庄市秦皇岛纽约绵阳美国伊利诺斯芝加哥舟山芒廷维尤芜湖芝加哥苏州莆田莫斯科菏泽营口衡水衡阳衢州西宁西安诺沃克贵港贵阳赤峰运城连云港邢台邯郸郑州郴州重庆重庆市钱德勒长春长沙长治阳泉雅加达青岛香港特别行政区齐齐哈尔

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      沈阳化工大学材料科学与工程学院 沈阳 110142

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