数据融合技术在集员辨识中的应用  

Applications of Data Fusion to Set Membership Identification

作　　者：梁礼明[1] 万孟森[1] 李钟侠[1] 

机构地区：[1]江西理工大学机电工程学院,江西赣州341000

出　　处：《江西理工大学学报》2010年第1期47-50,共4页Journal of Jiangxi University of Science and Technology

摘　　要：集员估计算法是一种新型的、有效的系统估计方法,在控制领域越来越受到重视.通过多传感器数据融合的方法,可以减少单一传感器辨识目标的不确定性和模糊性,可以进一步提高辨识结果的准确性和精度.文中提出了一种新型的基于数据融合的集员估计算法可以用来减少各种检测误差带来的影响,提高辨识的速度和精度.得出一个更优的集员估计集.Set membership estimation algorithm is a new and effective system estimation method, which is becoming increasingly important in the control area.Multisensor data fusion is introduced to obtain higher accuracy of target recognition.The accuracy will be improved further if quality of information sources is examined at first. Set Member- ship Identification is taken in this paper to decrease different errors from detecting, which helps improve the speed and accuracy of identification.

关 键 词：数据融合 不确定性 集员辨识 

分 类 号：TP274[自动化与计算机技术—检测技术与自动化装置]