摘要
目标威胁度评估是潜艇作战中至关重要的环节,为降低评估的复杂度并提高准确度,根据威胁目标空间来源多样性,构建协同作战模式下多作战空间的潜艇威胁度评估指标。采用组合核主成分分析(KPCA)法对威胁目标进行信息特征提取,根据提取到的信息特征计算目标的威胁系数后对威胁目标实现评估与排序。仿真结果表明,相比单核主成分分析,基于该组合KPCA的模型可对威胁目标进行更准确高效的评估。
Target threat degree assessment is a crucial link in submarine operations.In order to reduce the complexity of the evaluation and improve the accuracy of evaluation,according to the diversity of the target space sources,the submarine threat degree assessment index of the multi combat space under the cooperative operation mode is constructed.The combined Kernel Principal Component Analysis(KPCA)is used to extract the information features of the threat targets,and the threat targets are evaluated and sorted after calculating the target’s threat coefficients.Simulation results show that,the submarine threat degree assessment model of the combined KPCA can evaluate the threat targets more accurately and efficiently compared with the mononuclear Principal Component Analysis(PCA).
作者
董雪
张德平
DONG Xue;ZHANG Deping(College of Computer Science and Technology,Nanjing University of Aeronautics and Astronautics,Nanjing 210016,China)
出处
《计算机工程》
CAS
CSCD
北大核心
2018年第11期40-45,共6页
Computer Engineering
基金
国家部委基金
关键词
威胁度评估
潜艇作战
核主成分分析
权重确定
协同作战
threat degree assessment
submarine combat
Kernel Principal Component Analysis(KPCA)
weight determination
cooperative combat