@inproceedings{b91cd0863f374df7987b0ec1c8823322,
title = "Active and Passive Radar Target Fusion Recognition Method Based on Bayesian Network",
abstract = "Multi-sensor fusion recognition technology can make full use of the complementarity of information between sensors to reduce the influence of interference improves the success rate of target recognition, and has been widely used in the domain of radar target recognition. The multi-sensor fusion recognition methods that commonly used include Bayesian network, D-S evidence theory and so on, among which the Bayesian network has attracted extensive attention as not only it has a solid probability theory foundation but its structure and parameters can be learned. This paper proposes a fusion recognition method for active and passive radar target, the recognition results of active and passive radar targets are fused by the Bayesian network. The results show that the recognition success rate of using fusion recognition method based on Bayesian network is increased by 9.1\%, 4.8\% and 2.2\% compared with that using recognition methods for only active radar target and only passive radar target and fusion recognition method based on D-S evidence theory, which proves the feasibility and effectiveness of the fusion recognition method based on Bayesian network.",
keywords = "Bayesian network, fusion recognition, radar target recognition, recognition methods for only active radar target and only passive radar target",
author = "Ruoyun Li and Yuxi Zhang and Jinping Sun",
note = "Publisher Copyright: {\textcopyright} 2022 IEEE.; 15th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, CISP-BMEI 2022 ; Conference date: 05-11-2022 Through 07-11-2022",
year = "2022",
doi = "10.1109/CISP-BMEI56279.2022.9980098",
language = "英语",
series = "Proceedings - 2022 15th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, CISP-BMEI 2022",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
editor = "Xin Chen and Lin Cao and Qingli Li and Yan Wang and Lipo Wang",
booktitle = "Proceedings - 2022 15th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, CISP-BMEI 2022",
address = "美国",
}