面向智能态势认知的战场数据编码描述方法

Description and Coding Method of Battlefield Data for Intelligent Situation Cognition

提出了一种面向时序特征的战场态势描述方法,旨在从复杂、异构、高维且快速增长的战场数据中提取关键要素,将其转化为面向智能认知模型的规范化输入,通过将战场环境、作战实体、作战任务等的静态属性和时序动态特征进行规范化编码,以有效描述战场态势关键特征,压缩编码长度并降低数据冗余,将所提面向时序特征的战场态势编码描述方法应用于智能态势认知模型,对于提高智能认知模型的鲁棒性和适用性,具有较强的实用价值.

A method of battlefield situation description based on sequential features is proposed,which aims at extracting key elements from complex,heterogeneous and high-dimensional battlefield data,and transforming them into standardized input information oriented to intelligent cognitive models.The static attributes and sequential dynamic features of battlefield environment,combat entities and battle tasks are normalized and encoded.Thus,the key features of battlefield situation are e?ectively described,the coding length is compressed and the data redundancy is reduced.The proposed battlefield situation description method for time series features is applied to the intelligent situation recognition model,which has strong practical value for improving the robustness and applicability of intelligent situation recognition models.