摘要
为了优化多传感器信息融合方法,提出了一种基于Vague集的多传感器信息融合方法。首先定义了改进的Vague集的相似度量方法,通过层次分析法确定了各传感器的权重。然后定义了各目标与正负理想目标的距离,利用相对贴近度来确定最佳方案。最后通过仿真实例说明了该方法的有效性和实用性。
In order to optimize the multi-sensor information fusion method, a new method for multi-senor information fusion was proposed based on Vague sets. Firstly, an improved similarity measure method based on Vague sets was defined, and the weight of each sensor was determined by analytic hierarchy process. Secondly, the distance between each object and positive, negative ideal objects was defined, and the optimal scheme was determined by the relative closeness degree. Finally, a simulation examples in the paper showed that the method was effective and feasible.
出处
《模糊系统与数学》
CSCD
北大核心
2016年第2期177-183,共7页
Fuzzy Systems and Mathematics
基金
国家自然科学基金资助项目(11301159)
关键词
模糊集
VAGUE集
多传感器
信息融合
贴近度
Fuzzy Sets
Vague Sets
Multi-sensor
Information Fusion
Relative Closeness Degree
