首页 | 本学科首页   官方微博 | 高级检索  
     

基于WLS-KF的GPS非线性动态滤波研究
引用本文:齐小强,廉保旺,薛喆.基于WLS-KF的GPS非线性动态滤波研究[J].现代电子技术,2011,34(9):87-89.
作者姓名:齐小强  廉保旺  薛喆
作者单位:西北工业大学电子信息学院,陕西西安,710129
摘    要:为了提高动态定位精度,将卡尔曼(KF)算法应用到GPS非线性动态定位解算中,提出加权最小二乘-卡尔曼滤波(WLS-KF)算法。通过加权最小二乘(WLS)算法得到近似的线性化模型,再将KF算法应用到这个线性化模型进行校正。因此既保持了KF算法能够对系统状态进行最优估算的优点,同时对各个测量值进行了联系制约,具有更高的精度。结果表明,这种方法精度介于EKF和UKF之间,且实现容易,预测可靠,具有实际应用价值。

关 键 词:全球定位系统  卡尔曼滤波  加权最小二乘  非线性

GPS Nonlinear Dynamic Filter Algorithm Based on Weighted Least Squares-Kalman Filter
QI Xiao-qiang,LIAN Bao-wang,XUE Zhe.GPS Nonlinear Dynamic Filter Algorithm Based on Weighted Least Squares-Kalman Filter[J].Modern Electronic Technique,2011,34(9):87-89.
Authors:QI Xiao-qiang  LIAN Bao-wang  XUE Zhe
Affiliation:QI Xiao-qiang,LIAN Bao-wang,XUE Zhe(School of Electronic and Information,Northwestern Polytechnical University,Xi'an 710129,China)
Abstract:In order to improve the positioning accuracy,the weighted least squares-Kalman filter(WLS-KF)algorithm is proposed by applying Kalman filter(KF) into GPS nonlinear dynamic filter.An approximate linear system is formed from the WLS algorithm and regulated by KF.Thus it can keep the advantages of that the KF algorithm can optimally estimate the system status,restrict and contact each measured value.The results show that the accuracy range of this algorithm between EKF and UKF has reliable prediction and pract...
Keywords:GPS  Kalman filter  weighted least squares  nonlinear  
本文献已被 CNKI 维普 万方数据 等数据库收录!
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号