A NOVEL AZIMUTH SUPER-RESOLUTION METHOD BASE ON PARAMETER SEARCHING

Wen Feng Guo; Jin Peng Guo; Shao Qiang Chang; Quan Hua Liu

doi:10.1049/icp.2021.0817

A NOVEL AZIMUTH SUPER-RESOLUTION METHOD BASE ON PARAMETER SEARCHING

Wen Feng Guo
, Jin Peng Guo
, Shao Qiang Chang^*
, Quan Hua Liu

^*此作品的通讯作者

信息与电子学院

Beijing Institute of Technology

科研成果: 书/报告/会议事项章节 › 会议稿件 › 同行评审

摘要

Radar azimuth super-resolution has always been a hotspot in the field of radar detection. In this paper, a novel azimuth super-resolution algorithm base on parameter searching is proposed by searching the optimal target azimuth parameters iteratively based on least squares criterion. Particle swarm optimization is used to speed up the iteration. The proposed algorithm does not rely on prior knowledge which result in better adaptation and robustness. Simulation results show that the proposed method can effectively improve the resolution performance under low signal-to-noise ratio (SNR) conditions. The maximum resolution can be increased by 12.5 times, when SNR is no less than 10dB.

源语言	英语
主期刊名	IET Conference Proceedings
出版商	Institution of Engineering and Technology
页	374-378
页数	5
卷	2020
版本	9
ISBN（电子版）	9781839535406
DOI	https://doi.org/10.1049/icp.2021.0817
出版状态	已出版 - 2020
活动	5th IET International Radar Conference, IET IRC 2020 - Virtual, Online 期限: 4 11月 2020 → 6 11月 2020

会议

会议	5th IET International Radar Conference, IET IRC 2020
市	Virtual, Online
时期	4/11/20 → 6/11/20

访问文件

10.1049/icp.2021.0817

其它文件与链接

链接到 Scopus 的出版物

引用此

@inproceedings{c1cf8c5486144c73a67eeb17db9e7cf4,

title = "A NOVEL AZIMUTH SUPER-RESOLUTION METHOD BASE ON PARAMETER SEARCHING",

abstract = "Radar azimuth super-resolution has always been a hotspot in the field of radar detection. In this paper, a novel azimuth super-resolution algorithm base on parameter searching is proposed by searching the optimal target azimuth parameters iteratively based on least squares criterion. Particle swarm optimization is used to speed up the iteration. The proposed algorithm does not rely on prior knowledge which result in better adaptation and robustness. Simulation results show that the proposed method can effectively improve the resolution performance under low signal-to-noise ratio (SNR) conditions. The maximum resolution can be increased by 12.5 times, when SNR is no less than 10dB.",

keywords = "AZIMUTH SUPER-RESOLUTION, LEAST SQUARES ESTIMATION, PARAMETER SEARCHING",

author = "Guo, \{Wen Feng\} and Guo, \{Jin Peng\} and Chang, \{Shao Qiang\} and Liu, \{Quan Hua\}",

note = "Publisher Copyright: {\textcopyright} 2020 IET Conference Proceedings. All rights reserved.; 5th IET International Radar Conference, IET IRC 2020 ; Conference date: 04-11-2020 Through 06-11-2020",

year = "2020",

doi = "10.1049/icp.2021.0817",

language = "English",

volume = "2020",

pages = "374--378",

booktitle = "IET Conference Proceedings",

publisher = "Institution of Engineering and Technology",

address = "United Kingdom",

edition = "9",

}

TY - GEN

T1 - A NOVEL AZIMUTH SUPER-RESOLUTION METHOD BASE ON PARAMETER SEARCHING

AU - Guo, Wen Feng

AU - Guo, Jin Peng

AU - Chang, Shao Qiang

AU - Liu, Quan Hua

PY - 2020

Y1 - 2020

N2 - Radar azimuth super-resolution has always been a hotspot in the field of radar detection. In this paper, a novel azimuth super-resolution algorithm base on parameter searching is proposed by searching the optimal target azimuth parameters iteratively based on least squares criterion. Particle swarm optimization is used to speed up the iteration. The proposed algorithm does not rely on prior knowledge which result in better adaptation and robustness. Simulation results show that the proposed method can effectively improve the resolution performance under low signal-to-noise ratio (SNR) conditions. The maximum resolution can be increased by 12.5 times, when SNR is no less than 10dB.

AB - Radar azimuth super-resolution has always been a hotspot in the field of radar detection. In this paper, a novel azimuth super-resolution algorithm base on parameter searching is proposed by searching the optimal target azimuth parameters iteratively based on least squares criterion. Particle swarm optimization is used to speed up the iteration. The proposed algorithm does not rely on prior knowledge which result in better adaptation and robustness. Simulation results show that the proposed method can effectively improve the resolution performance under low signal-to-noise ratio (SNR) conditions. The maximum resolution can be increased by 12.5 times, when SNR is no less than 10dB.

KW - AZIMUTH SUPER-RESOLUTION

KW - LEAST SQUARES ESTIMATION

KW - PARAMETER SEARCHING

UR - https://www.scopus.com/pages/publications/85174649982

U2 - 10.1049/icp.2021.0817

DO - 10.1049/icp.2021.0817

M3 - Conference contribution

AN - SCOPUS:85174649982

VL - 2020

SP - 374

EP - 378

BT - IET Conference Proceedings

PB - Institution of Engineering and Technology

T2 - 5th IET International Radar Conference, IET IRC 2020

Y2 - 4 November 2020 through 6 November 2020

ER -

A NOVEL AZIMUTH SUPER-RESOLUTION METHOD BASE ON PARAMETER SEARCHING

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