舰艇编队的反导作战能力直接关系着编队的生存能力,而导弹目标类型识别是反导作战的基础。针对舰艇编队反导作战对导弹类型识别的具体战术要求,建立了反舰导弹分类及特征模型,分析了编队反导作战目标类型综合识别流程。结合粗糙集理论与自适应神经模糊推理,设计了一种基于粗糙自适应神经模糊推理(RAN-FIS)的导弹类型识别方法,提高了识别效率。根据LMS(least-mean square)算法设计了RANFIS的参数估计方法,该参数估计方法根据实际输出信号与网络输出信号之间的误差调整参数取值,能够根据已有反舰导弹样本的特征属性以及类型确定参数。仿真结果显示,所设计的导弹类型识别方法能够很好的识别海战场上出现的反舰导弹的类型。 The anti-missile capability of the naval formation is directly related to the survivability of the formation and the target type identification of the missile is the basis of the anti-missile combat. Aiming at the specific tactical requirements of missile formation in naval vessel formation for missile defense, this paper established classification and characteristic model of anti-ship missile, and analyzed the process of integrated identification of target type in formation of anti-missile defense. Combining Rough Set theory and adaptive neuro-fuzzy inference, a RAN-FIS-based missile type identification method is designed to improve the recognition efficiency. According to the LMS (least-mean square) algorithm, a parameter estimation method of RANFIS is designed. The parameter estimation method adjusts parameters according to the error between the actual output signal and the network output signal. Based on the characteristic attributes of the existing anti-ship missile samples and Type determines the parameter. Simulation results show that the proposed missile type identification method can well identify the types of anti-ship missiles that appear on the sea battlefield.