基于Kalman滤波和相关分析的分段多传感器测量  

Multi-sensor Measurement in Sections Based on Kalman Filter and Correlation Analysis

作　　者：陈渝光[1,2] 边晓彬[2] 周桐[2] 李新[2] 

机构地区：[1]汽车零部件制造与检测技术教育部重点实验室,重庆400050 [2]重庆理工大学电子信息与自动化学院,重庆400050

出　　处：《武汉理工大学学报》2010年第24期98-101,共4页Journal of Wuhan University of Technology

基　　金：重庆市教委应用技术研究项目(KJ090604)

摘　　要：针对单一传感器测量精度低、可靠性差和不能判断测量点间情况等局限性,提出了一种基于Kalman滤波和相关分析的分段多传感器测量方法。该方法很好地结合了Kalman递归滤波数据融合和相关分析的优势,避免了Kalman滤波在数学模型和噪声统计特性方面的缺点和局限性,提高了数据测量的精度和可靠性,并可以对测量点间异常信息进行判断。从开发的动态载荷轨道特征参数测量装置的数据处理可以看出,这种算法是有效的,效果也是十分明显的。A new method of multi-sensor measurement in sections based on kalman filter and correlation analysis is proposed,aiming at the problems of poor measurement precision,poor reliability,without estimating the status between measurement points for single sensor.It absorbs well the advantages both the data fusion based on kalman recursive filter and correlation analysis,with which the precision and reliability are enhanced and the status between the points can be estimated also.It avoids the limitation of kalman filter on math model and noise statistics characteristic at the same time.A character parameters measurement device of a dynamic load track was developed in succession.The data process results of the device demonstrated that the method is effective and the effect is significant.

关 键 词：分段测量 数据处理 多传感器 KALMAN滤波 相关分析 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]