模糊神经网络与证据理论的飞机目标敌我识别

为满足复杂环境下目标敌我属性识别能力，提出了一种基于模糊神经网络（FNN：Fuzzy Neural Networks）和证据理论的新敌我识别方法。该方法利用模糊神经网络和证据理
论信息的处理能力，将敌我识别器(IFF:Identification Friend -or-Foe）、电子支援措施(ESM:Electronic Warfare Support Measure)、雷达及红外获取的信息融合,进行敌我识别。
仿真结果表明，该方法的识别能力明显优于单一模糊神经网络分类器，识别率达0.994，同时具有很强的容错性和一定的抗干扰能力，更适合战场需要。

Fuzzy Neural Networks and D-S Theory Used in Friend and Foe Identification of Aircraft Target

In order to satisfiy the complex battlefield environment,we raise a n ew method to realize friend and foe identification.Using the ablity of fuzzy neural networks and D-S theory in information processing,fusing the information ac q uired from IFF(Identification Friend-or-Foe),ESM(Electronic Warfare Support M easure),radar and infrared,the identification is realized.The simulation results show that the recognition abilit y of the method is superior to a single FNN(Fuzzy Neural Networks),classifier r ecognition rate is 0.978.And it also has a strong fault-tolerance and a certain d egree of immunity,it better suited to the battlefield needs.