基于贝叶斯推理的海战场空中目标意图分层识别方法

Hierarchical Recognition Method of Hostile Air-targets in Sea Battlefields Based on Bayesian Deduction

针对海战场敌方空中目标意图识别方法都是一次性完成空中目标的意图识别,会在运算过程中带来消耗时间较多、效率较低的问题展开深入研究,在给出了海战场敌方空中目标相关特征参数计算和筛选公式的基础上,结合目标意图特点,依据指挥员的思维逻辑,提出了一种基于贝叶斯推理的海战场敌方空中目标意图分层识别新方法。该方法运用分层思想实现对更关注的目标意图更快捷的贝叶斯推理识别,可作为常规方法的简化过程,因此,可减少消耗时间,提高识别效率。基于实测数据的仿真实验验证了所提方法的有效性。

Nowadays,the intention recognition methods of hostile air-targets in sea battlefields are all executed to complete without being divided by several different periods or lays. However,the problem of time cost is comparatively long and efficiency is comparatively low in the process and operation periods is brought in. Aimed at this problem,some deep researches are carried out in the paper. On the basis of the calculation and choosing formulas of relative feature parameters of the hostile air-targets in sea battlefields are suggested,connected with their intention characteristics,according to the logic of thoughts of commanders,a new hierarchical intention recognition method of the hostile airtargets in sea battlefields based on Bayesian Deduction is proposed. In the method,the divided lays ideas and Bayesian Deduction are utilized to realize more concerned targets intentions recognition more quickly. The proposed method can be considered as a simple processing of the conventional method,resulting in the lost time can be reduced and the recognition efficiency can be improved. Simulation results with real datum proves the validity of the proposed method.