摘要
针对多只传感器对某一特性指标进行测量实验的数据融合问题,利用信息理论中的信息熵,提出了一种新的多传感器数据的融合方法。该方法以最小化各传感器测量数据的信息熵之和为目标函数,通过求解极值问题,得到了多传感器数据的融合结果。可以较好地避免受主观因素影响的关系矩阵,充分利用实验数据,防止有效数据的丢失。该算法简洁稳定,可用于提高智能仪表的测量准确度和改善智能仪表的抗干扰能力。
Aimed at data fusion of multi-sensor experiment on some characteristic index,a new fusion method for multi-sensors data is brought forward by applying the entropy in the theory of information. The object function is gotten by minimizing the sum of all sensors＇ entropy, the fusion result is obtained by solving the extremum problem. The new method may avoid the relationship matrix influenced by subject factors, make full use of the data of experiment,and prevent the effective data from losing. The approach is simple and stable. It is used to improve the accuracy and anti-interference of intelligent instruments.
出处
《传感器与微系统》
CSCD
北大核心
2008年第5期64-65,68,共3页
Transducer and Microsystem Technologies
基金
教育部人文社科规划资助项目(05JA630024)
江西省工业攻关计划资助项目([2005]224)
关键词
多传感器
数据融合
熵
智能仪表
multi-sensor
data fusion
entropy
intelligent instruments
