A TRACK ASSOCIATION ALGORITHM BASED ON MOTION DYNAMICS FEATURES IN ENTOMOLOGICAL RADAR

Biao Li; Hanzhe Liu; Tianran Zhang; Jiong Cai; Rui Wang

doi:10.1049/icp.2024.1319

A TRACK ASSOCIATION ALGORITHM BASED ON MOTION DYNAMICS FEATURES IN ENTOMOLOGICAL RADAR

Biao Li, Hanzhe Liu, Tianran Zhang, Jiong Cai, Rui Wang^*

^*Corresponding author for this work

School of Information and Electronics

Research output: Contribution to journal › Conference article › peer-review

Abstract

When tracking densely distributed targets such as insects, the traditional trajectory association algorithm exhibits poor correlation performance, leading to a decline in multi-target tracking efficiency. In this paper, based on the behavioral characteristics of insects gathering and co-orienting during aerial flight, a motion dynamic feature-assisted multi-target tracking method is proposed. Firstly, a three-dimensional biological distribution state matrix is constructed through spatial gridization. Then, a three-dimensional circular convolution is employed to estimate the target's motion dynamic feature, assisting in multi-target trajectory initialization. Finally, the improvement effect of the method on trajectory tracking accuracy is validated through simulations and migration insect data.

Original language	English
Pages (from-to)	1571-1575
Number of pages	5
Journal	IET Conference Proceedings
Volume	2023
Issue number	47
DOIs	https://doi.org/10.1049/icp.2024.1319
Publication status	Published - 2023
Event	IET International Radar Conference 2023, IRC 2023 - Chongqing, China Duration: 3 Dec 2023 → 5 Dec 2023

Keywords

ENTOMOLOGICAL RADAR
MULTITARGET TRACKING
TRACK ASSOCIATION
TRACK INITIATION

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10.1049/icp.2024.1319

Cite this

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title = "A TRACK ASSOCIATION ALGORITHM BASED ON MOTION DYNAMICS FEATURES IN ENTOMOLOGICAL RADAR",

abstract = "When tracking densely distributed targets such as insects, the traditional trajectory association algorithm exhibits poor correlation performance, leading to a decline in multi-target tracking efficiency. In this paper, based on the behavioral characteristics of insects gathering and co-orienting during aerial flight, a motion dynamic feature-assisted multi-target tracking method is proposed. Firstly, a three-dimensional biological distribution state matrix is constructed through spatial gridization. Then, a three-dimensional circular convolution is employed to estimate the target's motion dynamic feature, assisting in multi-target trajectory initialization. Finally, the improvement effect of the method on trajectory tracking accuracy is validated through simulations and migration insect data.",

keywords = "ENTOMOLOGICAL RADAR, MULTITARGET TRACKING, TRACK ASSOCIATION, TRACK INITIATION",

author = "Biao Li and Hanzhe Liu and Tianran Zhang and Jiong Cai and Rui Wang",

note = "Publisher Copyright: {\textcopyright} The Institution of Engineering & Technology 2023.; IET International Radar Conference 2023, IRC 2023 ; Conference date: 03-12-2023 Through 05-12-2023",

year = "2023",

doi = "10.1049/icp.2024.1319",

language = "English",

volume = "2023",

pages = "1571--1575",

journal = "IET Conference Proceedings",

issn = "2732-4494",

publisher = "Institution of Engineering and Technology",

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T1 - A TRACK ASSOCIATION ALGORITHM BASED ON MOTION DYNAMICS FEATURES IN ENTOMOLOGICAL RADAR

AU - Li, Biao

AU - Liu, Hanzhe

AU - Zhang, Tianran

AU - Cai, Jiong

AU - Wang, Rui

N1 - Publisher Copyright: © The Institution of Engineering & Technology 2023.

PY - 2023

Y1 - 2023

N2 - When tracking densely distributed targets such as insects, the traditional trajectory association algorithm exhibits poor correlation performance, leading to a decline in multi-target tracking efficiency. In this paper, based on the behavioral characteristics of insects gathering and co-orienting during aerial flight, a motion dynamic feature-assisted multi-target tracking method is proposed. Firstly, a three-dimensional biological distribution state matrix is constructed through spatial gridization. Then, a three-dimensional circular convolution is employed to estimate the target's motion dynamic feature, assisting in multi-target trajectory initialization. Finally, the improvement effect of the method on trajectory tracking accuracy is validated through simulations and migration insect data.

AB - When tracking densely distributed targets such as insects, the traditional trajectory association algorithm exhibits poor correlation performance, leading to a decline in multi-target tracking efficiency. In this paper, based on the behavioral characteristics of insects gathering and co-orienting during aerial flight, a motion dynamic feature-assisted multi-target tracking method is proposed. Firstly, a three-dimensional biological distribution state matrix is constructed through spatial gridization. Then, a three-dimensional circular convolution is employed to estimate the target's motion dynamic feature, assisting in multi-target trajectory initialization. Finally, the improvement effect of the method on trajectory tracking accuracy is validated through simulations and migration insect data.

KW - ENTOMOLOGICAL RADAR

KW - MULTITARGET TRACKING

KW - TRACK ASSOCIATION

KW - TRACK INITIATION

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U2 - 10.1049/icp.2024.1319

DO - 10.1049/icp.2024.1319

M3 - Conference article

AN - SCOPUS:85203192994

SN - 2732-4494

VL - 2023

SP - 1571

EP - 1575

JO - IET Conference Proceedings

JF - IET Conference Proceedings

IS - 47

T2 - IET International Radar Conference 2023, IRC 2023

Y2 - 3 December 2023 through 5 December 2023

ER -

A TRACK ASSOCIATION ALGORITHM BASED ON MOTION DYNAMICS FEATURES IN ENTOMOLOGICAL RADAR

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Keywords

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