A robust target intention recognition method based on dynamic bayesian network

Qunli Xiao; Yuanna Liu; Xinyang Deng; Wen Jiang

doi:10.1109/CCDC52312.2021.9602205

A robust target intention recognition method based on dynamic bayesian network

Qunli Xiao
, Yuanna Liu
, Xinyang Deng
, Wen Jiang

School of Electronics and Information

Northwestern Polytechnical University Xian

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

7 Scopus citations

Abstract

The enemy's tactical intention is one of the important basis for the commander's decision. The accuracy and timeliness of the judgment of the enemy's tactical intention will directly affect the correctness and effectiveness of our combat command decisions. In this paper, a robust target intention recognition method based on dynamic bayesian network is proposed. Self-organizing feature maps is introduced to preprocess the track information to estimate the stable heading of the target and various characteristic factors related to the air target combat intention are integrated to construct a dynamic bayesian network model for the recognition of the enemy's target intention. In the simulated air combat scene, the proposed method can effectively realize combat intention recognition.

Original language	English
Title of host publication	Proceedings of the 33rd Chinese Control and Decision Conference, CCDC 2021
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	6846-6851
Number of pages	6
ISBN (Electronic)	9781665440899
DOIs	https://doi.org/10.1109/CCDC52312.2021.9602205
State	Published - 2021
Event	33rd Chinese Control and Decision Conference, CCDC 2021 - Kunming, China Duration: 22 May 2021 → 24 May 2021

Publication series

Name	Proceedings of the 33rd Chinese Control and Decision Conference, CCDC 2021

Conference

Conference	33rd Chinese Control and Decision Conference, CCDC 2021
Country/Territory	China
City	Kunming
Period	22/05/21 → 24/05/21

Keywords

Dynamic bayesian network
Intention recognition
Self-organizing feature maps

Access to Document

10.1109/CCDC52312.2021.9602205

Cite this

Xiao, Q., Liu, Y., Deng, X., & Jiang, W. (2021). A robust target intention recognition method based on dynamic bayesian network. In Proceedings of the 33rd Chinese Control and Decision Conference, CCDC 2021 (pp. 6846-6851). (Proceedings of the 33rd Chinese Control and Decision Conference, CCDC 2021). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CCDC52312.2021.9602205

@inproceedings{fac742faf3f6481092480130cf123bc9,

title = "A robust target intention recognition method based on dynamic bayesian network",

abstract = "The enemy's tactical intention is one of the important basis for the commander's decision. The accuracy and timeliness of the judgment of the enemy's tactical intention will directly affect the correctness and effectiveness of our combat command decisions. In this paper, a robust target intention recognition method based on dynamic bayesian network is proposed. Self-organizing feature maps is introduced to preprocess the track information to estimate the stable heading of the target and various characteristic factors related to the air target combat intention are integrated to construct a dynamic bayesian network model for the recognition of the enemy's target intention. In the simulated air combat scene, the proposed method can effectively realize combat intention recognition.",

keywords = "Dynamic bayesian network, Intention recognition, Self-organizing feature maps",

author = "Qunli Xiao and Yuanna Liu and Xinyang Deng and Wen Jiang",

note = "Publisher Copyright: {\textcopyright} 2021 IEEE.; 33rd Chinese Control and Decision Conference, CCDC 2021 ; Conference date: 22-05-2021 Through 24-05-2021",

year = "2021",

doi = "10.1109/CCDC52312.2021.9602205",

language = "英语",

series = "Proceedings of the 33rd Chinese Control and Decision Conference, CCDC 2021",

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

pages = "6846--6851",

booktitle = "Proceedings of the 33rd Chinese Control and Decision Conference, CCDC 2021",

}

Xiao, Q, Liu, Y, Deng, X & Jiang, W 2021, A robust target intention recognition method based on dynamic bayesian network. in Proceedings of the 33rd Chinese Control and Decision Conference, CCDC 2021. Proceedings of the 33rd Chinese Control and Decision Conference, CCDC 2021, Institute of Electrical and Electronics Engineers Inc., pp. 6846-6851, 33rd Chinese Control and Decision Conference, CCDC 2021, Kunming, China, 22/05/21. https://doi.org/10.1109/CCDC52312.2021.9602205

A robust target intention recognition method based on dynamic bayesian network. / Xiao, Qunli; Liu, Yuanna; Deng, Xinyang et al.
Proceedings of the 33rd Chinese Control and Decision Conference, CCDC 2021. Institute of Electrical and Electronics Engineers Inc., 2021. p. 6846-6851 (Proceedings of the 33rd Chinese Control and Decision Conference, CCDC 2021).

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

TY - GEN

T1 - A robust target intention recognition method based on dynamic bayesian network

AU - Xiao, Qunli

AU - Liu, Yuanna

AU - Deng, Xinyang

AU - Jiang, Wen

PY - 2021

Y1 - 2021

N2 - The enemy's tactical intention is one of the important basis for the commander's decision. The accuracy and timeliness of the judgment of the enemy's tactical intention will directly affect the correctness and effectiveness of our combat command decisions. In this paper, a robust target intention recognition method based on dynamic bayesian network is proposed. Self-organizing feature maps is introduced to preprocess the track information to estimate the stable heading of the target and various characteristic factors related to the air target combat intention are integrated to construct a dynamic bayesian network model for the recognition of the enemy's target intention. In the simulated air combat scene, the proposed method can effectively realize combat intention recognition.

AB - The enemy's tactical intention is one of the important basis for the commander's decision. The accuracy and timeliness of the judgment of the enemy's tactical intention will directly affect the correctness and effectiveness of our combat command decisions. In this paper, a robust target intention recognition method based on dynamic bayesian network is proposed. Self-organizing feature maps is introduced to preprocess the track information to estimate the stable heading of the target and various characteristic factors related to the air target combat intention are integrated to construct a dynamic bayesian network model for the recognition of the enemy's target intention. In the simulated air combat scene, the proposed method can effectively realize combat intention recognition.

KW - Dynamic bayesian network

KW - Intention recognition

KW - Self-organizing feature maps

UR - https://www.scopus.com/pages/publications/85125199694

U2 - 10.1109/CCDC52312.2021.9602205

DO - 10.1109/CCDC52312.2021.9602205

M3 - 会议稿件

AN - SCOPUS:85125199694

T3 - Proceedings of the 33rd Chinese Control and Decision Conference, CCDC 2021

SP - 6846

EP - 6851

BT - Proceedings of the 33rd Chinese Control and Decision Conference, CCDC 2021

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 33rd Chinese Control and Decision Conference, CCDC 2021

Y2 - 22 May 2021 through 24 May 2021

ER -

Xiao Q, Liu Y, Deng X , Jiang W. A robust target intention recognition method based on dynamic bayesian network. In Proceedings of the 33rd Chinese Control and Decision Conference, CCDC 2021. Institute of Electrical and Electronics Engineers Inc. 2021. p. 6846-6851. (Proceedings of the 33rd Chinese Control and Decision Conference, CCDC 2021). doi: 10.1109/CCDC52312.2021.9602205

A robust target intention recognition method based on dynamic bayesian network

Abstract

Publication series

Conference

Keywords

Access to Document

Other files and links

Fingerprint

Cite this