Cooperative tactical recognition of dual-aircraft formation under incomplete information in BVR air combat

被引：0
|
作者：
Meng G. [1 ]
Zhang H. [1 ]
Piao H. [2 ]
Zhou M. [1 ]
机构：
[1] School of Automation, Shenyang Aerospace University, Shenyang
[2] AVIC Shenyang Aircraft Design and Research Institute, Shenyang
来源：
Beijing Hangkong Hangtian Daxue Xuebao/Journal of Beijing University of Aeronautics and Astronautics | 2023年 / 49卷 / 02期
基金：
中国国家自然科学基金;
关键词：
cooperative air combat; cooperative tactics of dual-aircraft formation; dynamic Bayesian network; parameter learning; tactical recognition;
D O I：
10.13700/j.bh.1001-5965.2021.0251
中图分类号：
学科分类号：
摘要：
In the process of beyond-visual-range (BVR) air combat, due to the limitation of detection equipment performance and enemy interference, the target information is easy to get lost, which makes it difficult to identify the enemy’s cooperative air combat tactics in real time. A method of cooperative tactical recognition is proposed based on dynamic Bayesian network (DBN) and parameter learning. Firstly, the cooperative tactics of dual-aircraft formation in BVR air combat are analyzed. According to the functional tasks of leader and wingman, the current situation information and fighter maneuver, a DBN recognition model is established. Then, to improve the recognition rate of the model, the expected maximum parameter learning method is used to optimize the network parameters. Finally, based on the auto-regressive model, the missing target information is repaired, and the reasoning algorithm of cooperative tactical recognition under incomplete information is proposed. The simulation results show that the method of cooperative tactical recognition has high recognition accuracy and good real-time performance for cooperative tactics under incomplete information in BVR air combat. © 2023 Beijing University of Aeronautics and Astronautics (BUAA). All rights reserved.
引用
收藏
页码：284 / 294
页数：10
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