运用Vague集进行多传感器目标识别  

Applying Vague set for multi-sensor object recognition

作　　者：万树平[1] 

机构地区：[1]江西财经大学信息管理学院,江西南昌330013

出　　处：《传感器与微系统》2011年第1期58-59,78,共3页Transducer and Microsystem Technologies

基　　金：国家自然科学基金资助项目(10626029);教育部人文社科基金资助项目(09YGC630107);江西省教育厅科技计划资助项目(GJJ10123;GJJ10122);江西省教育科学"十一五"规划项目(09YB267)

摘　　要：针对具有多个特征指标的多传感器目标识别问题,采用Vague集表达目标特征的不确定信息,提出了一种新的多传感器目标识别方法。定义两Vague集之间的加权Hamming距离和相似度,建立了Vague集表达的多传感器目标识别模型,通过最小化各目标类型的Vague度优化模型客观地确定了各特征的权重,利用相似度给出目标识别算法。实例分析表明方法的有效性。Aiming at the problem of muhi-sensor object recognition with multiple characteristics, Vague set is used to represent the fuzzy measurement information of object characteristic. A new method of multi-sensor object recognition is proposed. The method defines the weighted Hamming distance and similarity degree between two Vague sets, and constructs the model of object recognition represented by Vague set. The weights of characteristics are objectively determined by the optimization model of minimizing the Vague degree of each object type. The algorithm of object recognition is given according to the similarity degree. The example analysis shows that the method is effective.

关 键 词：多传感器目标识别 VAGUE集 加权Hamming距离 相似度 

分 类 号：TP274.2[自动化与计算机技术—检测技术与自动化装置]