来袭鱼雷类型识别指标提取与算法设计

Indices Extraction and Algorithm Design for Recognizing Type of Incoming Torpedo

针对水面舰艇在鱼雷防御行动中难以准确识别来袭鱼雷类型的问题,该文从战技特征层信息入手,提炼出14个与鱼雷类型识别密切相关的证据指标;根据获取性难易程度将指标进行分类。针对登普斯特-谢弗证据理论的不足,引入了一种改进的融合算法,提出了对证据进行确定性信息预处理的方式,建立了完整的信息融合算法流程。仿真结果表明,通过提取证据指标和改进融合算法,该文算法对鱼雷类型的识别精度比传统方法大大提高,从而为水面舰艇采取有针对性的鱼雷防御措施提供了重要保障。

In view of the actuality that the surface ship can＇t exactly recognize the type of incoming torpedo in defense action,fourteen indices correlating to recognize torpedo types are extracted and sorted in acquirable difficulty.In view of some deficiencies in Dempster-Shafer theory,a sort of improved data fusion algorithm is established.A pretreatment method for certainty information is introduced,and the entire flow chart of information fusion is designed.The simulation result proves the algorithm here is more accurate than the traditional method.It can ensure surface ship take action exactly to defend against incoming torpedos.