中文摘要：

这份报纸基于雷达十字节(RCS ) 学习雷达目标识别的问题观察顺序。首先，作者计算 RCS 观察顺序的分离小浪变换并且提取包含五个部件的有效统计特征向量。这五个部件代表雷达目标的五个不同特征。第二，作者建立一个珍视集合的模型代表在特征向量和雷达目标的真实性之间的关系。由珍视集合的鉴定方法，作者能估计系统参数，识别标准基于被给。以便说明建议识别方法的效率，广泛的模拟最后被给假设真目标是锥平截头体和假目标的 RCS 是通常分布式的。结果证明珍视集合的鉴定方法让更高的识别比传统的模糊分类方法和证据的推理方法评价。

英文摘要：

This paper studies the problem of radar target recognition based on radar cross section （RCS） observation sequence. First, the authors compute the discrete wavelet transform of RCS ob- servation sequence and extract a valid statistical feature vector containing five components. These five components represent five different features of the radar target. Second, the authors establish a set-valued model to represent the relation between the feature vector and the authenticity of the radar target. By set-valued identification method, the authors can estimate the system parameter, based on which the recognition criteria is given. In order to illustrate the efficiency of the proposed recognition method, extensive simulations are given finally assuming that the true target is a cone frustum and the RCS of the false target is normally distributed. The results show that the set-valued identification method has a higher recognition rate than the traditional fuzzy classification method and evidential reasoning method.