摘要
为消除误差和随机干扰对测量数据的影响,利用扩展卡尔曼滤波算法对测量数据进行处理,并提出基于扩展卡尔曼滤波算法的不可信点判断方法对测量数据进行野值剔除。两种方法结合运用,可以在保留数据特征的基础上,提高数据的精度,更好地反映测量目标的性能。
In order to eliminate errors and random disturbances on the measured data, uses the extended Kalman filter to process the measurement data, and proposes the trusted judgment based on extended Kalman filter to remove the measurement data outliers.The two methods applied in combination can improve the accuracy of the data on the basis of data retention characteristics, and better reflect the performance of the measurement target.
出处
《现代计算机》
2012年第5期8-10,共3页
Modern Computer
关键词
扩展卡尔曼滤波
野值
数据处理
Extended Kalman Filter
Outliers
Data Processing
