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
N1 - Publisher Copyright:
© 2021 IEEE.
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 - http://www.scopus.com/inward/record.url?scp=85125199694&partnerID=8YFLogxK
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 -