Study on the Effectiveness Evaluation Method of Formation beyond Visual Range Air Combat Based on Genetic BP Neural Network
The Beyond Visual Range (BVR) air combat has become the most important mode of modern air combat. In this paper, a new model is set up combining situation assessment model and the formation combat capacity model. Genetic BP Neural Network is used for the effectiveness evaluation of BVR Firstly, the main factors of the situation assessment in BVR air combat are proposed and analyzed. Secondly, Analytic Hierarchy Process (AHP) model of combat capacity assessment in BVR is established. The main factors are obtained by using Principal Component Analysis (PCA)to select input variables. A new model is presented as an AHP model integrated from the two above models, then, combine Genetic Algorithms(GA) with BP neural network,using GAs global to search the optimized BP network structure parameters, overcome the local convergence and solve other issues of BP algorithm effectively. Using the new model to get the input variables, GA-BP hybrid modeling is applied to effectiveness evaluation of BVR Finally, a typical 2-VS-4 air combat example is presented to verify the models availability. The results show the order of the attack of the reds that make the effectiveness evaluation maximum. The results of the numerical example show that the model can limit the artificial factors, making the solution more objective and creditable. Data link plays an important role in BVR air combat.
Beyond Visual Range air combat Genetic BP Neural Network effectiveness fighter formation Principal Component Analysis situation supremacy data link
Liang Xiao Huang Jun Zhou Yaoyao
Beijing University of Aeronautics and Astronautics, Beijing 100191, P.R China China Academy of Aerospace Aerodynamics, Beijing, 100074, China
国际会议
2010 Asia-Pacific International Symposium on Aerospace Technology(2010 亚太航空航天技术研讨会 APISAT 2010)
西安
英文
673-677
2010-09-01（万方平台首次上网日期，不代表论文的发表时间）