Research on Passive Localization Method with High Detection Rate

Dongpo Zhang; Xuan Hou; Lei Ding; Lina Zhu; Nan Cheng; Tom H. Luan

doi:10.1109/VTC2023-Fall60731.2023.10333564

Research on Passive Localization Method with High Detection Rate

Dongpo Zhang
, Xuan Hou
, Lei Ding
, Lina Zhu
, Nan Cheng
, Tom H. Luan

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

1 Scopus citations

Abstract

Passive localization is commonly achieved through the direction finding and positioning technique, which uses a airborne or ground multi-station angle measuring system to intersect pointing lines for fast and omnidirectional positioning. However, as the number of targets increases, so does the occurrence of false points. This poses a challenge to the positioning performance of system, requiring the prompt elimination of false points. To address the issue, we propose a high detection rate passive localization method based on density peak clustering (DPC). In this method, a suitable non-ideal location model is established, and improved density peak clustering is utilized to achieve data association and target localization. Simulation results confirm the proposed positioning method's superior performance and adaptation to the non-ideal conditions of multi-target localization.

Original language	English
Title of host publication	2023 IEEE 98th Vehicular Technology Conference, VTC 2023-Fall - Proceedings
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9798350329285
DOIs	https://doi.org/10.1109/VTC2023-Fall60731.2023.10333564
State	Published - 2023
Externally published	Yes
Event	98th IEEE Vehicular Technology Conference, VTC 2023-Fall - Hong Kong, China Duration: 10 Oct 2023 → 13 Oct 2023

Publication series

Name	IEEE Vehicular Technology Conference
ISSN (Print)	1550-2252

Conference

Conference	98th IEEE Vehicular Technology Conference, VTC 2023-Fall
Country/Territory	China
City	Hong Kong
Period	10/10/23 → 13/10/23

Keywords

Density peak clustering
Direction finding and positioning
Passive localization

Access to Document

10.1109/VTC2023-Fall60731.2023.10333564

Cite this

@inproceedings{025883b89bd146eaaca035d09dc7dfba,

title = "Research on Passive Localization Method with High Detection Rate",

abstract = "Passive localization is commonly achieved through the direction finding and positioning technique, which uses a airborne or ground multi-station angle measuring system to intersect pointing lines for fast and omnidirectional positioning. However, as the number of targets increases, so does the occurrence of false points. This poses a challenge to the positioning performance of system, requiring the prompt elimination of false points. To address the issue, we propose a high detection rate passive localization method based on density peak clustering (DPC). In this method, a suitable non-ideal location model is established, and improved density peak clustering is utilized to achieve data association and target localization. Simulation results confirm the proposed positioning method's superior performance and adaptation to the non-ideal conditions of multi-target localization.",

keywords = "Density peak clustering, Direction finding and positioning, Passive localization",

author = "Dongpo Zhang and Xuan Hou and Lei Ding and Lina Zhu and Nan Cheng and Luan, \{Tom H.\}",

note = "Publisher Copyright: {\textcopyright} 2023 IEEE.; 98th IEEE Vehicular Technology Conference, VTC 2023-Fall ; Conference date: 10-10-2023 Through 13-10-2023",

year = "2023",

doi = "10.1109/VTC2023-Fall60731.2023.10333564",

language = "英语",

series = "IEEE Vehicular Technology Conference",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

booktitle = "2023 IEEE 98th Vehicular Technology Conference, VTC 2023-Fall - Proceedings",

}

Zhang, D, Hou, X, Ding, L, Zhu, L, Cheng, N & Luan, TH 2023, Research on Passive Localization Method with High Detection Rate. in 2023 IEEE 98th Vehicular Technology Conference, VTC 2023-Fall - Proceedings. IEEE Vehicular Technology Conference, Institute of Electrical and Electronics Engineers Inc., 98th IEEE Vehicular Technology Conference, VTC 2023-Fall, Hong Kong, China, 10/10/23. https://doi.org/10.1109/VTC2023-Fall60731.2023.10333564

Research on Passive Localization Method with High Detection Rate. / Zhang, Dongpo; Hou, Xuan; Ding, Lei et al.
2023 IEEE 98th Vehicular Technology Conference, VTC 2023-Fall - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2023. (IEEE Vehicular Technology Conference).

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

TY - GEN

T1 - Research on Passive Localization Method with High Detection Rate

AU - Zhang, Dongpo

AU - Hou, Xuan

AU - Ding, Lei

AU - Zhu, Lina

AU - Cheng, Nan

AU - Luan, Tom H.

PY - 2023

Y1 - 2023

N2 - Passive localization is commonly achieved through the direction finding and positioning technique, which uses a airborne or ground multi-station angle measuring system to intersect pointing lines for fast and omnidirectional positioning. However, as the number of targets increases, so does the occurrence of false points. This poses a challenge to the positioning performance of system, requiring the prompt elimination of false points. To address the issue, we propose a high detection rate passive localization method based on density peak clustering (DPC). In this method, a suitable non-ideal location model is established, and improved density peak clustering is utilized to achieve data association and target localization. Simulation results confirm the proposed positioning method's superior performance and adaptation to the non-ideal conditions of multi-target localization.

AB - Passive localization is commonly achieved through the direction finding and positioning technique, which uses a airborne or ground multi-station angle measuring system to intersect pointing lines for fast and omnidirectional positioning. However, as the number of targets increases, so does the occurrence of false points. This poses a challenge to the positioning performance of system, requiring the prompt elimination of false points. To address the issue, we propose a high detection rate passive localization method based on density peak clustering (DPC). In this method, a suitable non-ideal location model is established, and improved density peak clustering is utilized to achieve data association and target localization. Simulation results confirm the proposed positioning method's superior performance and adaptation to the non-ideal conditions of multi-target localization.

KW - Density peak clustering

KW - Direction finding and positioning

KW - Passive localization

UR - https://www.scopus.com/pages/publications/85181173555

U2 - 10.1109/VTC2023-Fall60731.2023.10333564

DO - 10.1109/VTC2023-Fall60731.2023.10333564

M3 - 会议稿件

AN - SCOPUS:85181173555

T3 - IEEE Vehicular Technology Conference

BT - 2023 IEEE 98th Vehicular Technology Conference, VTC 2023-Fall - Proceedings

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 98th IEEE Vehicular Technology Conference, VTC 2023-Fall

Y2 - 10 October 2023 through 13 October 2023

ER -

Research on Passive Localization Method with High Detection Rate

Abstract

Publication series

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Keywords

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