基于DS的电子战多信息PCA融合方案

Multi-Information PCA Fusion Scheme of Electronic Warfare Based on DS

该文提出一种新型主成份分析(PCA)电子战信息一体化融合方案。该方案基于信息融合DS理论,采用PCA分析法对数据进行收集和降维处理;再对特征层数据建立基本信任分配函数,实现基于特征的数据融合;最后对电子战系统信息进行智能诊断和挖掘等,有效实现电子战系统中故障检测和分离。进一步,通过大数据挖掘对设备状态进行评估,及时发送给控制系统,实现作战过程中对作战战略的合理指导、预警管控,从而对多系统协同工作提供有力保障。

In this paper, a new type of principal component analysis (PCA) for electronic warfare information integration fusion scheme is presented. Based on DS theory of information fusion, the PCA method is used to collect data and reduce dimensions, and the basic trust distribution function is established for feature layer data to realize further based data fusion. The electronic warfare system information is intelligently diagnosed and mined to effectively achieve the fault detection and separation of electronic warfare system. Furthermore, the device status is evaluated and timely sent the control system through the big data mining, thus implementing the reasonable guidance and early warning and control for operational strategy in warfare procedure.