An Effective Method for Weak Multi-target Detection and Tracking in Clutter Environment

Chun Li; Xia Bai; Juan Zhao; Tao Shan

doi:10.1145/3529570.3529593

An Effective Method for Weak Multi-target Detection and Tracking in Clutter Environment

Chun Li, Xia Bai^*, Juan Zhao, Tao Shan

^*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

2 Citations (Scopus)

Abstract

Weak target detection and tracking is a difficult problem, especially in the case of multi-target and strong clutters. Track-before-detect (TBD) is the common method to deal with this problem, and this paper proposes a new effective method based on TBD. Firstly, keystone transform (KT) and phase gradient autofocus (PGA) are used for migration compensation to improve the signal-to-noise ratio (SNR) of moving targets. Then dynamic programming based TBD (DP-TBD) with joint intensity-spatial CFAR (J-CA-CFAR) is presented for noncoherent integration, where J-CA-CFAR uses both intensity and spatial information to achieve automatic target detection. Finally, the effectiveness of the proposed method was demonstrated by experimental results on real data.

Original language	English
Title of host publication	ICDSP 2022 - 2022 6th International Conference on Digital Signal Processing
Publisher	Association for Computing Machinery
Pages	134-139
Number of pages	6
ISBN (Electronic)	9781450395809
DOIs	https://doi.org/10.1145/3529570.3529593
Publication status	Published - 25 Feb 2022
Event	6th International Conference on Digital Signal Processing, ICDSP 2022 - Virtual, Online, China Duration: 25 Feb 2022 → 27 Feb 2022

Publication series

Name	ACM International Conference Proceeding Series
Volume	Par F180471

Conference

Conference	6th International Conference on Digital Signal Processing, ICDSP 2022
Country/Territory	China
City	Virtual, Online
Period	25/02/22 → 27/02/22

Keywords

constant false alarm rate (CFAR)
dynamic programming (DP)
strong clutter
track-before-detect (TBD)
weak target detection

Access to Document

10.1145/3529570.3529593

Cite this

Li, C., Bai, X., Zhao, J., & Shan, T. (2022). An Effective Method for Weak Multi-target Detection and Tracking in Clutter Environment. In ICDSP 2022 - 2022 6th International Conference on Digital Signal Processing (pp. 134-139). (ACM International Conference Proceeding Series; Vol. Par F180471). Association for Computing Machinery. https://doi.org/10.1145/3529570.3529593

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title = "An Effective Method for Weak Multi-target Detection and Tracking in Clutter Environment",

abstract = "Weak target detection and tracking is a difficult problem, especially in the case of multi-target and strong clutters. Track-before-detect (TBD) is the common method to deal with this problem, and this paper proposes a new effective method based on TBD. Firstly, keystone transform (KT) and phase gradient autofocus (PGA) are used for migration compensation to improve the signal-to-noise ratio (SNR) of moving targets. Then dynamic programming based TBD (DP-TBD) with joint intensity-spatial CFAR (J-CA-CFAR) is presented for noncoherent integration, where J-CA-CFAR uses both intensity and spatial information to achieve automatic target detection. Finally, the effectiveness of the proposed method was demonstrated by experimental results on real data.",

keywords = "constant false alarm rate (CFAR), dynamic programming (DP), strong clutter, track-before-detect (TBD), weak target detection",

author = "Chun Li and Xia Bai and Juan Zhao and Tao Shan",

note = "Publisher Copyright: {\textcopyright} 2022 ACM.; 6th International Conference on Digital Signal Processing, ICDSP 2022 ; Conference date: 25-02-2022 Through 27-02-2022",

year = "2022",

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day = "25",

doi = "10.1145/3529570.3529593",

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Li, C, Bai, X , Zhao, J & Shan, T 2022, An Effective Method for Weak Multi-target Detection and Tracking in Clutter Environment. in ICDSP 2022 - 2022 6th International Conference on Digital Signal Processing. ACM International Conference Proceeding Series, vol. Par F180471, Association for Computing Machinery, pp. 134-139, 6th International Conference on Digital Signal Processing, ICDSP 2022, Virtual, Online, China, 25/02/22. https://doi.org/10.1145/3529570.3529593

An Effective Method for Weak Multi-target Detection and Tracking in Clutter Environment. / Li, Chun; Bai, Xia ; Zhao, Juan et al.
ICDSP 2022 - 2022 6th International Conference on Digital Signal Processing. Association for Computing Machinery, 2022. p. 134-139 (ACM International Conference Proceeding Series; Vol. Par F180471).

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

TY - GEN

T1 - An Effective Method for Weak Multi-target Detection and Tracking in Clutter Environment

AU - Li, Chun

AU - Bai, Xia

AU - Zhao, Juan

AU - Shan, Tao

PY - 2022/2/25

Y1 - 2022/2/25

N2 - Weak target detection and tracking is a difficult problem, especially in the case of multi-target and strong clutters. Track-before-detect (TBD) is the common method to deal with this problem, and this paper proposes a new effective method based on TBD. Firstly, keystone transform (KT) and phase gradient autofocus (PGA) are used for migration compensation to improve the signal-to-noise ratio (SNR) of moving targets. Then dynamic programming based TBD (DP-TBD) with joint intensity-spatial CFAR (J-CA-CFAR) is presented for noncoherent integration, where J-CA-CFAR uses both intensity and spatial information to achieve automatic target detection. Finally, the effectiveness of the proposed method was demonstrated by experimental results on real data.

AB - Weak target detection and tracking is a difficult problem, especially in the case of multi-target and strong clutters. Track-before-detect (TBD) is the common method to deal with this problem, and this paper proposes a new effective method based on TBD. Firstly, keystone transform (KT) and phase gradient autofocus (PGA) are used for migration compensation to improve the signal-to-noise ratio (SNR) of moving targets. Then dynamic programming based TBD (DP-TBD) with joint intensity-spatial CFAR (J-CA-CFAR) is presented for noncoherent integration, where J-CA-CFAR uses both intensity and spatial information to achieve automatic target detection. Finally, the effectiveness of the proposed method was demonstrated by experimental results on real data.

KW - constant false alarm rate (CFAR)

KW - dynamic programming (DP)

KW - strong clutter

KW - track-before-detect (TBD)

KW - weak target detection

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U2 - 10.1145/3529570.3529593

DO - 10.1145/3529570.3529593

M3 - Conference contribution

AN - SCOPUS:85133764731

T3 - ACM International Conference Proceeding Series

SP - 134

EP - 139

BT - ICDSP 2022 - 2022 6th International Conference on Digital Signal Processing

PB - Association for Computing Machinery

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Y2 - 25 February 2022 through 27 February 2022

ER -

An Effective Method for Weak Multi-target Detection and Tracking in Clutter Environment

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