MULTI-DIMENSIONAL FEATURE-ASSISTED MULTI-TARGET TRACKING ALGORITHM IN STRONG CLUTTER ENVIRONMENT

Meng Gao; Wenfeng Guo; Zhennan Liang; Haibo Liu; Yuanyuan Song

doi:10.1049/icp.2023.1273

MULTI-DIMENSIONAL FEATURE-ASSISTED MULTI-TARGET TRACKING ALGORITHM IN STRONG CLUTTER ENVIRONMENT

Meng Gao, Wenfeng Guo, Zhennan Liang, Haibo Liu, Yuanyuan Song^*

^*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

Aiming at the multi-target tracking problem under clutter environment, a multi-dimensional feature-assisted multi-target tracking algorithm is proposed. The algorithm makes full use of the differences between the target and clutter measurements in multi-dimensional observations such as distance distribution, kinetic characteristics, and amplitude characteristics, accurately extracts multi-dimensional features, constructs comprehensive feature factor, and classifies and identifies the measurements. Minimize clutter and false alarm measurements, and achieve multi-target tracking in strong clutter scenarios. The performance of the algorithm is verified by the real radar measurement data, and the verification results show that the proposed algorithm can achieve accurate multi-target tracking in strong clutter environment, and has better tracking performance than other traditional feature-assisted tracking algorithms.

Original language	English
Title of host publication	IET Conference Proceedings
Publisher	Institution of Engineering and Technology
Pages	684-689
Number of pages	6
Volume	2022
Edition	17
ISBN (Electronic)	9781839537776
DOIs	https://doi.org/10.1049/icp.2023.1273
Publication status	Published - 2022
Event	2022 International Conference on Radar Systems, RADAR 2022 - Edinburgh, Virtual, United Kingdom Duration: 24 Oct 2022 → 27 Oct 2022

Conference

Conference	2022 International Conference on Radar Systems, RADAR 2022
Country/Territory	United Kingdom
City	Edinburgh, Virtual
Period	24/10/22 → 27/10/22

Keywords

FEATURE-ASSISTED TRACKING
MULTI-TARGET TRACKING
STRONG CLUTTER

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10.1049/icp.2023.1273

Cite this

@inproceedings{a8ff4a140c9344768c5e081edaddb1b8,

title = "MULTI-DIMENSIONAL FEATURE-ASSISTED MULTI-TARGET TRACKING ALGORITHM IN STRONG CLUTTER ENVIRONMENT",

abstract = "Aiming at the multi-target tracking problem under clutter environment, a multi-dimensional feature-assisted multi-target tracking algorithm is proposed. The algorithm makes full use of the differences between the target and clutter measurements in multi-dimensional observations such as distance distribution, kinetic characteristics, and amplitude characteristics, accurately extracts multi-dimensional features, constructs comprehensive feature factor, and classifies and identifies the measurements. Minimize clutter and false alarm measurements, and achieve multi-target tracking in strong clutter scenarios. The performance of the algorithm is verified by the real radar measurement data, and the verification results show that the proposed algorithm can achieve accurate multi-target tracking in strong clutter environment, and has better tracking performance than other traditional feature-assisted tracking algorithms.",

keywords = "FEATURE-ASSISTED TRACKING, MULTI-TARGET TRACKING, STRONG CLUTTER",

author = "Meng Gao and Wenfeng Guo and Zhennan Liang and Haibo Liu and Yuanyuan Song",

note = "Publisher Copyright: {\textcopyright} IET Conference Proceedings. All rights reserved.; 2022 International Conference on Radar Systems, RADAR 2022 ; Conference date: 24-10-2022 Through 27-10-2022",

year = "2022",

doi = "10.1049/icp.2023.1273",

language = "English",

volume = "2022",

pages = "684--689",

booktitle = "IET Conference Proceedings",

publisher = "Institution of Engineering and Technology",

address = "United Kingdom",

edition = "17",

}

Gao, M, Guo, W, Liang, Z , Liu, H & Song, Y 2022, MULTI-DIMENSIONAL FEATURE-ASSISTED MULTI-TARGET TRACKING ALGORITHM IN STRONG CLUTTER ENVIRONMENT. in IET Conference Proceedings. 17 edn, vol. 2022, Institution of Engineering and Technology, pp. 684-689, 2022 International Conference on Radar Systems, RADAR 2022, Edinburgh, Virtual, United Kingdom, 24/10/22. https://doi.org/10.1049/icp.2023.1273

TY - GEN

T1 - MULTI-DIMENSIONAL FEATURE-ASSISTED MULTI-TARGET TRACKING ALGORITHM IN STRONG CLUTTER ENVIRONMENT

AU - Gao, Meng

AU - Guo, Wenfeng

AU - Liang, Zhennan

AU - Liu, Haibo

AU - Song, Yuanyuan

PY - 2022

Y1 - 2022

N2 - Aiming at the multi-target tracking problem under clutter environment, a multi-dimensional feature-assisted multi-target tracking algorithm is proposed. The algorithm makes full use of the differences between the target and clutter measurements in multi-dimensional observations such as distance distribution, kinetic characteristics, and amplitude characteristics, accurately extracts multi-dimensional features, constructs comprehensive feature factor, and classifies and identifies the measurements. Minimize clutter and false alarm measurements, and achieve multi-target tracking in strong clutter scenarios. The performance of the algorithm is verified by the real radar measurement data, and the verification results show that the proposed algorithm can achieve accurate multi-target tracking in strong clutter environment, and has better tracking performance than other traditional feature-assisted tracking algorithms.

AB - Aiming at the multi-target tracking problem under clutter environment, a multi-dimensional feature-assisted multi-target tracking algorithm is proposed. The algorithm makes full use of the differences between the target and clutter measurements in multi-dimensional observations such as distance distribution, kinetic characteristics, and amplitude characteristics, accurately extracts multi-dimensional features, constructs comprehensive feature factor, and classifies and identifies the measurements. Minimize clutter and false alarm measurements, and achieve multi-target tracking in strong clutter scenarios. The performance of the algorithm is verified by the real radar measurement data, and the verification results show that the proposed algorithm can achieve accurate multi-target tracking in strong clutter environment, and has better tracking performance than other traditional feature-assisted tracking algorithms.

KW - FEATURE-ASSISTED TRACKING

KW - MULTI-TARGET TRACKING

KW - STRONG CLUTTER

UR - http://www.scopus.com/inward/record.url?scp=85174643826&partnerID=8YFLogxK

U2 - 10.1049/icp.2023.1273

DO - 10.1049/icp.2023.1273

M3 - Conference contribution

AN - SCOPUS:85174643826

VL - 2022

SP - 684

EP - 689

BT - IET Conference Proceedings

PB - Institution of Engineering and Technology

T2 - 2022 International Conference on Radar Systems, RADAR 2022

Y2 - 24 October 2022 through 27 October 2022

ER -

MULTI-DIMENSIONAL FEATURE-ASSISTED MULTI-TARGET TRACKING ALGORITHM IN STRONG CLUTTER ENVIRONMENT

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Keywords

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