Adaptive fuze-warhead coordination method based on BP artificial neural network

作     者：Peng Hou Yang Pei Yu-xue Ge Peng Hou;Yang Pei;Yu-xue Ge

作者机构：School of AeronauticsNorthwestern Polytechnical UniversityXi'an710072ShaanxiChina 

出 版 物：《Defence Technology（防务技术）》 (Defence Technology)

年 卷 期：2023年第29卷第11期

页      面：117-133页

核心收录：

学科分类：12[管理学] 1201[管理学-管理科学与工程(可授管理学、工学学位)] 081104[工学-模式识别与智能系统] 08[工学] 082603[工学-火炮、自动武器与弹药工程] 0826[工学-兵器科学与技术] 0835[工学-软件工程] 0811[工学-控制科学与工程] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

主　　题：Aircraft vulnerability Fuze-warhead coordination BP artificial neural network Damage probability Initiation delay 

摘      要：The appropriate fuze-warhead coordination method is important to improve the damage efficiency of air defense missiles against aircraft targets. In this paper, an adaptive fuze-warhead coordination method based on the Back Propagation Artificial Neural Network(BP-ANN) is proposed, which uses the parameters of missile-target intersection to adaptively calculate the initiation delay. The damage probabilities at different radial locations along the same shot line of a given intersection situation are calculated, so as to determine the optimal detonation position. On this basis, the BP-ANN model is used to describe the complex and highly nonlinear relationship between different intersection parameters and the corresponding optimal detonating point position. In the actual terminal engagement process, the fuze initiation delay is quickly determined by the constructed BP-ANN model combined with the missiletarget intersection parameters. The method is validated in the case of the single-shot damage probability evaluation. Comparing with other fuze-warhead coordination methods, the proposed method can produce higher single-shot damage probability under various intersection conditions, while the fuzewarhead coordination effect is less influenced by the location of the aim point.