RBUKF算法在GPS实时定位解算中的应用

Journal of Systems Engineering and Electronics ›› 2009, Vol. 31 ›› Issue (11): 2578-2581 .

RBUKF算法在GPS实时定位解算中的应用

刘江1,陆明泉2,王忠勇1

1. 郑州大学信息工程学院，河南郑州 450052； 2. 清华大学电子工程系，北京 100084

出版日期:2009-11-26 发布日期:2010-01-03

Application of RBUKF algorithm in realtime GPS position estimatin

LIU Jiang,LU Ming-quan,WANG Zhong-yong

1. Coll. of Information Engineering, Zhengzhou Univ., Zhengzhou 450052, China;2. Dept. of Electronic Engineering, Tsinghua Univ., Beijing 100084, China

Online:2009-11-26 Published:2010-01-03

摘要/Abstract

摘要：

迭代最小二乘法（iterative least square, ILS）是GPS实时定位解算中使用最为广泛的方法，而近年来扩展卡尔曼滤波（extended Kalman filter, EKF）和无轨迹卡尔曼滤波（unscented Kalman filter, UKF）也在定位解算中逐步得到应用。主要研究了UKF算法的改进型RBUKF算法在GPS实时定位解算中的应用。首先建立了滤波模型，并通过分析和调试得到了滤波器参数，最后使用真实卫星数据对算法进行了验证。实验结果表明：RBUKF算法的定位精度优于EKF和ILS，与UKF基本相同，而其计算量小于UKF和EKF。

Abstract:

The iterative least square (ILS) algorithm has been widely used in the realtime GPS position. Recently, the extended Kalman filter (EKF) and unscented Kalman filter (UKF) are proposed to use in this problem. The application of the RBUKF, an improved algorithm of UKF, in the realtime GPS position estimation is proposed. A filter model is constructed firstly. Then the proper parameters are acquired by analyzing and tuning. The real satellite data are used to test the algorithm finally. The result of the experiment shows that the accuracy of RBUKF is better than the EKF and ILS, while equals to the UKF, and its computational complexity is better than the UKF and EKF.

刘江1,陆明泉2,王忠勇1. RBUKF算法在GPS实时定位解算中的应用[J]. Journal of Systems Engineering and Electronics, 2009, 31(11): 2578-2581 .

LIU Jiang,LU Ming-quan,WANG Zhong-yong. Application of RBUKF algorithm in realtime GPS position estimatin[J]. Journal of Systems Engineering and Electronics, 2009, 31(11): 2578-2581 .