一种参数区间交叉类型的目标识别方法

针对参数区间为交叉类型的目标识别问题，提出了基于直觉模糊集和云模型的逼近理想点（TOPSIS）识别方法。构建了包含个体类和交叉类的目标数据库模型，根据云模型的多步估计算法，得到未知目标相对已知目标类的确定度，提出了确定度向隶属度和非隶属度的转化方法，基于直觉模糊熵计算特征属性的动态权重，形成了去模糊距离测度的TOPSIS识别方法，应用于辐射源信号识别。仿真结果表明，所提方法对参数区间交叉类型的目标正确识别率较高，具有一定的实际应用价值。 

A methodology for target recognition with parameters of interval cross type

Aimed at the problem of target recognition with parameters of interval cross type, the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method for target recognition based on intuitionistic fuzzy set and cloud model is proposed in this paper. The target database model including individual class and cross class is constructed. According to the multi-step estimation algorithm for cloud model, the certainty degree of an unknown target over a known target class is obtained, and the transformation algorithm from certainty degree to membership and non-membership degree is proposed. The dynamic attribute weight is calculated based on intuitionistic fuzzy entropy. The TOPSIS recognition decision method of defuzzification distance measure is formed. The simulation results indicate that the proposed method has a high accuracy rate for target recognition with parameters of interval cross type and thus has a certain practical application value, when applied to radar emitter recognition.