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

^*Corresponding author for this work

School of Information and Electronics

Beijing Institute of Technology

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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.

Original language	English
Title of host publication	IET Conference Proceedings
Publisher	Institution of Engineering and Technology
Pages	374-378
Number of pages	5
Volume	2020
Edition	9
ISBN (Electronic)	9781839535406
DOIs	https://doi.org/10.1049/icp.2021.0817
Publication status	Published - 2020
Event	5th IET International Radar Conference, IET IRC 2020 - Virtual, Online Duration: 4 Nov 2020 → 6 Nov 2020

Conference

Conference	5th IET International Radar Conference, IET IRC 2020
City	Virtual, Online
Period	4/11/20 → 6/11/20

Keywords

AZIMUTH SUPER-RESOLUTION
LEAST SQUARES ESTIMATION
PARAMETER SEARCHING

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10.1049/icp.2021.0817

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@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",

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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

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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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