基于粗糙集-信息熵的辐射源威胁评估方法

为满足复杂电磁环境下战机对辐射源威胁等级判定算法的需求，将粗糙集理论引入对雷达辐射源威胁评估中，并结合信息熵理论构建一套完备的计算威胁度量值的数据处理模型，实现对辐射源威胁程度的定量表示，直观地评估辐射源的威胁程度。经典粗糙集理论难以应对在没有决策信息条件下的决策问题，采用信息熵的方法求取最大权重属性替代决策属性，拓展粗糙集的适用范围。模型直接基于数据驱动得到辐射源的威胁度量值，易于实现并具备良好的时效性，减少系统对先验信息的要求与主观赋值带来的影响。仿真结果表明,该方法可以快速、准确地实现对辐射源威胁的评估。 

Radiator threat evaluating method based on rough set and information entropy

In order to meet the need of threat ranking arithmetic of air radar emitter in complex electronic environment, the rough set theory is introduced into radar radiator threat evaluation. A self-contained data processing model for computing threat metric values is established to realize the quantitative representation of the radiator threat degree, thus allowing evaluating the threat degree of emitter straightforward. The information entropy is applied to determine the attribute with the maximal weight instead of decision one, solving the decision-making problem when there is no prior knowledge, which can be used to extend the range of application of classical rough set. This model is based on data-boost method to acquire the radiator threat metric values directly, which is easily realized and has favorable time-efficient feature. The method reduces the demand of system for prior information and avoids the effect introduced by subjective assignments. The simulation results show that the method has good ability to accomplish target threat assessment fleetly and exactly.