摘要
本文着重研究舰船雷达弱目标的模糊分类问题，讨论了利用Ｋｏｈｏｎｅｎ自组织网络来实现各类目标的二维隶属函数生成．介绍了弱目标回波特征抽取和模糊分类器的设计，并将模糊分类结果和经典的Ｋ－ＮＮ分类结果进行了比较，得到低信杂比条件下多类弱目标的良好分类效果．本文所提出的模糊分类算法具有很强的通用性．
A fuzzy sets-based method for radar weak target classification is proposed and studied. The membership functions of different radar targets are generated by using a two dimensional self-organizing feature mapping network. The kernel estimation of probability distribution and the consistent transformation between probability and possibility are employed by using the network. The problem of feature extraction for radar weak targets is simply discussed. The given testing results show that a high level of robustness and simultaneously a high accuracy of radar ship target classification have been reached by using the proposed fuzzy classification method. The method can be referred in other fuzzy pattern recognition areas.
出处
《电子学报》
EI
CAS
CSCD
北大核心
1996年第6期67-71,共5页
Acta Electronica Sinica
基金
国家自然科学基金
关键词
模糊分类
雷达目标
神经网络
目标识别雷达
Fuzzy classification, Radar target, Neural networks, Membership function
