DSmT理论在综合敌我识别中的应用

战场环境的复杂性要求使用多种传感器对战场目标进行综合敌我识别，而综合敌我识别有待解决的基础性难题之一是如何对异类传感器输出的不确定性信息进行有效处理。针对一包含雷达、红外、电子支援措施和敌我识别器等传感器的综合敌我识别系统，对异类传感器敌我识别过程进行分析，根据其特点提出采用DSmT理论进行决策级融合，同时针对每类传感器构造不同的基本置信指派方法，并进行了算法仿真。实验结果证实了该方法的有效性。

Application of DSmT in integrated identification of friend-or-foe

Under a complex battlefield environment, the multi-sensor integrated identification of friend-or-foe based on multi-sensor information may be needed. The effective processing of uncertain information from different sensors is a fundamental problem to be solved. For the integrated system of friend-or-foe identification consists of radar, infrared, electronic support measure (ESM) and a device of friend or foe identification, the identification process of different sensors is analyzed. Then, the fusion rule based on Dezert-Smarandache theory (DSmT) is used to achieve the decision level fusion. At the same time, different methods for constructing the basic belief assignment function are introduced. The simulation results show the availability of this method.