摘要
为采用多个传感器对某一目标特性进行多次测量,提出一种改进的动态加权多传感器数据融合算法。利用模糊集合理论中的隶属函数构造各观测值的支持度矩阵,通过增加矩阵维数度量观测数据在整个观测区间的相互支持程度,采用矩阵特征向量的稳定理论分配融合权重,得到数据融合估计的最终表达式。仿真结果表明,与同类方法相比,该方法的融合精度较高,具有较好的稳健性。
In the case of multi-sensors measurement of many times on some characteristic index,a new fusion method is proposed.A membership function in fuzzy set is used to measure the mutual support degree of observation values,and the integrated support degree of data from various sensors is measured through an augmented support degree matrix.According to this augmented matrix＇s maximum modulus eigenvectors,corresponding weight coefficients of all the observation values are allocated,hence,the final expression of data fusion is obtained.An example and a simulation are used to compare the proposed method with another two similar fusion methods.Result shows that this method has both higher precision and strong ability of stableness.
出处
《计算机工程》
CAS
CSCD
北大核心
2011年第11期97-99,共3页
Computer Engineering
基金
国家自然科学基金资助项目(60672172)
中央高校基本科研基金资助项目(ZXH2009C007)
中国民航大学科研基金资助项目(08CAUC_E04)
关键词
多传感器
数据融合
扩维矩阵
支持度
multi-sensors
data fusion
augmented dimensional matrix
support degree
