| Citation: | MENG Guanglei, ZHANG Huimin, PIAO Haiyin, et al. Recognition of fighter maneuver in automatic flight training evaluation[J]. Journal of Beijing University of Aeronautics and Astronautics, 2020, 46(7): 1267-1274. doi: 10.13700/j.bh.1001-5965.2019.0445(in Chinese)
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An improved online recognition method for fighter maneuver based on dynamic Bayesian network is proposed for automatic flight training evaluation. First, the maneuver characteristics of instrument, simple stunt and complex stunt flight are analyzed. Then, according to the causal relationship between maneuver and characteristic parameters during flight process of fighter, a dynamic Bayesian network model for maneuver recognition is established, which overcomes the shortcomings of traditional methods, such as the need for roll angle information which is difficultly obtained in real time through radar detection in actual flight training. At the same time, the computational complexity is reduced by designing the online invocation mechanism of the model. Experimental results show that this method has high fighter maneuver recognition rate and good real-time performance, and can meet the needs of online application.
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