首先分析了Ｋｏｈｏｎｅｎ神经网络算法及其识别机理。结合飞机目标识别实际情况，借鉴人脑从粗分到细分的思想，提出了基于ＫＮＮ—ＭＬＦＮＮ网络组分类器的飞机目标分类方法。应用于五种飞机目标的识别结果表明：自组织神经网络的学习速度快，自学习能力强；ＫＮＮ—ＭＬＦＮＮ网络组分类器有高的分类精度。 Firstly, the Kohonen neural network algorithm and its recognition mechanism are analyzed. Combining with the actual situation of aircraft target recognition and using the idea of ​​human brain from rough to subdivision, this paper proposes an aircraft target classification method based on KNN-MLFNN network group classifier. The recognition results applied to the five aircraft targets show that self-organizing neural network has fast learning speed and self-learning ability, and KNN-MLFNN network group classifier has high classification accuracy.