Study on Elevation Estimation of Low-Angle Target in Meter-Wave Radar Based on Machine-Learning

Di Chen; Chengyu Hou

doi:10.1007/978-3-030-69066-3_40

Study on Elevation Estimation of Low-Angle Target in Meter-Wave Radar Based on Machine-Learning

Di Chen^*
, Chengyu Hou

^*Corresponding author for this work

School of Electronics and Information Engineering

Harbin Institute of Technology

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

Abstract

In these years, meter-wave radar has gotten more and more attention from the researchers all over the world for its advantages in anti-stealth. However, the beam width of meter-wave radar is wider because of the size of radar antenna's vertical aperture, and it makes the low-angle targets detecting and tracking more difficult, which has become one of the urgent problems in radar field. In this paper, the multipath effect in low-angle target detecting will be researched, and an elevation estimation algorithm of low-angle target in meter-wave radar based on machine-learning will be proposed.

Original language	English
Title of host publication	Artificial Intelligence for Communications and Networks - 2nd EAI International Conference, AICON 2020, Proceedings
Editors	Shuo Shi, Liang Ye, Yu Zhang
Publisher	Springer Science and Business Media Deutschland GmbH
Pages	457-464
Number of pages	8
ISBN (Print)	9783030690656
DOIs	https://doi.org/10.1007/978-3-030-69066-3_40
State	Published - 2021
Event	2nd EAI International Conference on Artificial Intelligence for Communications and Networks, AICON 2020 - Harbin, China Duration: 19 Dec 2020 → 20 Dec 2020

Publication series

Name	Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST
Volume	356 LNICST
ISSN (Print)	1867-8211
ISSN (Electronic)	1867-822X

Conference

Conference	2nd EAI International Conference on Artificial Intelligence for Communications and Networks, AICON 2020
Country/Territory	China
City	Harbin
Period	19/12/20 → 20/12/20

Keywords

Elevation estimation
Meter-wave radar
Reflected echoes cancelling

Access to Document

10.1007/978-3-030-69066-3_40

Cite this

Chen, D., & Hou, C. (2021). Study on Elevation Estimation of Low-Angle Target in Meter-Wave Radar Based on Machine-Learning. In S. Shi, L. Ye, & Y. Zhang (Eds.), Artificial Intelligence for Communications and Networks - 2nd EAI International Conference, AICON 2020, Proceedings (pp. 457-464). (Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST; Vol. 356 LNICST). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-030-69066-3_40

Chen, Di ; Hou, Chengyu. / Study on Elevation Estimation of Low-Angle Target in Meter-Wave Radar Based on Machine-Learning. Artificial Intelligence for Communications and Networks - 2nd EAI International Conference, AICON 2020, Proceedings. editor / Shuo Shi ; Liang Ye ; Yu Zhang. Springer Science and Business Media Deutschland GmbH, 2021. pp. 457-464 (Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST).

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title = "Study on Elevation Estimation of Low-Angle Target in Meter-Wave Radar Based on Machine-Learning",

abstract = "In these years, meter-wave radar has gotten more and more attention from the researchers all over the world for its advantages in anti-stealth. However, the beam width of meter-wave radar is wider because of the size of radar antenna's vertical aperture, and it makes the low-angle targets detecting and tracking more difficult, which has become one of the urgent problems in radar field. In this paper, the multipath effect in low-angle target detecting will be researched, and an elevation estimation algorithm of low-angle target in meter-wave radar based on machine-learning will be proposed.",

keywords = "Elevation estimation, Meter-wave radar, Reflected echoes cancelling",

author = "Di Chen and Chengyu Hou",

note = "Publisher Copyright: {\textcopyright} 2021, ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering.; 2nd EAI International Conference on Artificial Intelligence for Communications and Networks, AICON 2020 ; Conference date: 19-12-2020 Through 20-12-2020",

year = "2021",

doi = "10.1007/978-3-030-69066-3\_40",

language = "英语",

isbn = "9783030690656",

series = "Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST",

publisher = "Springer Science and Business Media Deutschland GmbH",

pages = "457--464",

editor = "Shuo Shi and Liang Ye and Yu Zhang",

booktitle = "Artificial Intelligence for Communications and Networks - 2nd EAI International Conference, AICON 2020, Proceedings",

address = "德国",

}

Chen, D & Hou, C 2021, Study on Elevation Estimation of Low-Angle Target in Meter-Wave Radar Based on Machine-Learning. in S Shi, L Ye & Y Zhang (eds), Artificial Intelligence for Communications and Networks - 2nd EAI International Conference, AICON 2020, Proceedings. Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST, vol. 356 LNICST, Springer Science and Business Media Deutschland GmbH, pp. 457-464, 2nd EAI International Conference on Artificial Intelligence for Communications and Networks, AICON 2020, Harbin, China, 19/12/20. https://doi.org/10.1007/978-3-030-69066-3_40

Study on Elevation Estimation of Low-Angle Target in Meter-Wave Radar Based on Machine-Learning. / Chen, Di; Hou, Chengyu.
Artificial Intelligence for Communications and Networks - 2nd EAI International Conference, AICON 2020, Proceedings. ed. / Shuo Shi; Liang Ye; Yu Zhang. Springer Science and Business Media Deutschland GmbH, 2021. p. 457-464 (Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST; Vol. 356 LNICST).

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

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AU - Chen, Di

AU - Hou, Chengyu

PY - 2021

Y1 - 2021

N2 - In these years, meter-wave radar has gotten more and more attention from the researchers all over the world for its advantages in anti-stealth. However, the beam width of meter-wave radar is wider because of the size of radar antenna's vertical aperture, and it makes the low-angle targets detecting and tracking more difficult, which has become one of the urgent problems in radar field. In this paper, the multipath effect in low-angle target detecting will be researched, and an elevation estimation algorithm of low-angle target in meter-wave radar based on machine-learning will be proposed.

AB - In these years, meter-wave radar has gotten more and more attention from the researchers all over the world for its advantages in anti-stealth. However, the beam width of meter-wave radar is wider because of the size of radar antenna's vertical aperture, and it makes the low-angle targets detecting and tracking more difficult, which has become one of the urgent problems in radar field. In this paper, the multipath effect in low-angle target detecting will be researched, and an elevation estimation algorithm of low-angle target in meter-wave radar based on machine-learning will be proposed.

KW - Elevation estimation

KW - Meter-wave radar

KW - Reflected echoes cancelling

UR - https://www.scopus.com/pages/publications/85104429732

U2 - 10.1007/978-3-030-69066-3_40

DO - 10.1007/978-3-030-69066-3_40

M3 - 会议稿件

AN - SCOPUS:85104429732

SN - 9783030690656

T3 - Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST

SP - 457

EP - 464

BT - Artificial Intelligence for Communications and Networks - 2nd EAI International Conference, AICON 2020, Proceedings

A2 - Shi, Shuo

A2 - Ye, Liang

A2 - Zhang, Yu

PB - Springer Science and Business Media Deutschland GmbH

T2 - 2nd EAI International Conference on Artificial Intelligence for Communications and Networks, AICON 2020

Y2 - 19 December 2020 through 20 December 2020

ER -

Chen D, Hou C. Study on Elevation Estimation of Low-Angle Target in Meter-Wave Radar Based on Machine-Learning. In Shi S, Ye L, Zhang Y, editors, Artificial Intelligence for Communications and Networks - 2nd EAI International Conference, AICON 2020, Proceedings. Springer Science and Business Media Deutschland GmbH. 2021. p. 457-464. (Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST). doi: 10.1007/978-3-030-69066-3_40

Study on Elevation Estimation of Low-Angle Target in Meter-Wave Radar Based on Machine-Learning

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Keywords

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