一种用于GPS/DR组合定位的非线性滤波算法

刘旭; 张其善; 杨东凯

一种用于GPS/DR组合定位的非线性滤波算法

北京航空航天大学电子信息工程学院, 北京 100083

详细信息

中图分类号: TN 967.2;U 491.512
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出版历程
- 收稿日期: 2006-03-09
- 网络出版日期: 2007-02-28

Nonlinear filter algorithm for GPS/DR integrated positioning

School of Electronics and Information Engineering, Beijing University of Aeronautics and Astronautics, Beijing 100083, China

摘要

摘要: 建立了适用于车辆导航系统的基于UKF(Unscented Kalman Filter)的GPS/DR(Global Positioning System/Dead Reckoning)组合定位滤波模型及算法.针对系统状态方程为线性、观测方程为非线性的特点,提出了一种将UKF和EKF(Extended Kalman Filter)相结合的非线性滤波算法.结合后的算法和原有UKF算法相比减少了在时间更新阶段的运算量,并且由于采用基于Unscented变换的思想来处理系统观测方程的非线性问题,避免了EKF引入的线性化误差,提高了滤波精度.仿真结果证明:算法在减少运算量的同时,仍具有较高的滤波精度,且明显优于EKF,因而能够满足车辆导航系统占用资源少、滤波精度高的要求.
- 航位推算法 /
- GPS /
- 组合导航 /
- 卡尔曼滤波
Abstract: A filter model and its algorithm based on UKF (unscented Kalman filter) for GPS/DR (global positioning system/dead reckoning) integrated positioning in land vehicle navigation system were established. Aiming at the system characteristic of linear state equation and nonlinear measurement equation, the algorithm which combines UKF with EKF (extended Kalman filter) was proposed. Compared with general UKF,the operation time used for the phase of time updating is less than that of general UKF. The error caused by the linearization of EKF is eliminated and the precision is improved contributing to processing the nonlinear problem with unscented transform. The simulation result demonstrates that the algorithm has better filtering precision than EKF, and reduces computing time, which is fit for integrated navigation system demanding for little resource and high precision.
- dead reckoning /
- GPS /
- integrated navigation /
- Kalman filtering

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参考文献(1)

[1] 房建成,申功勋,万德钧.自适应卡尔曼滤波器在陆地车辆导航中的应用[J].北京航空航天大学学报,1999,25(2):235-239 Fang Jiancheng, Shen Gongxun, Wan Dejun. Adaptive extended kalman filter model for integrated land vehicle navigation system [J]. Journal of Beijing University of Aeronautics and Astronautics, 1999, 25(2):235-239(in Chinese) [2] 郑平方,常青,张其善,等.车载GPS/DR组合导航系统数据融合算法研究[J].通信学报,2000,21(2):42-48 Zhen Pingfang, Chang Qing, Zhang Qishan, et al. The study of data fusion algorithm of GPS/DR integrated vehicular navigation system [J]. Journal of Communication, 2000, 21(2):42-48(in Chinese) [3] 寇艳红,张其善,李先亮.车载GPS/DR组合导航系统的信息融合新方案[J].遥测遥控,2002,23(1):7-12 Kou Yanhong, Zhang Qishan, Li Xianliang. New scheme of information fusion for GPS/DR integrated vehicle navigation system [J]. Journal of Telemetry, Tracking, and Command, 2002, 23(1):7-12 (in Chinese) [4] 寇艳红,张其善,李先亮.车载GPS/DR组合导航系统的数据融合算法[J].北京航空航天大学学报,2003,29(3):264-268 Kou Yanhong, Zhang Qishan, Li Xianliang. Data fusion algorithm for GPS/DR integrated vehicle navigation system [J]. Journal of Beijing University of Aeronautics and Astronautics, 2003, 29(3):264-268(in Chinese) [5] Julier S, Uhlmann J K. A new approach for filtering nonlinear systems The Proceedings of the American Control Conference. :IEEE Press, 1995:1628-1632 [6] Wan E A, Merwe R. The unscented kalman filter for nonlinear estimation Proc of IEEE Symposium 2000 on Adaptive Systems for Signal Processing, Communications, and Control Symposium. :IEEE Standard Office, 2000:153-158 [7] Wan E A, Merwe R. The square-root unscented kalman filter for state and parameter-estimation Proceedings. (ICASSP '01) 2001 IEEE International Conferenc. :IEEE Press, 2001:3461-3464 [8] Zhou H R, Kumar K S P. A current statistical model and adaptive algorithm for estimating maneuvering targets [J]. Journal of Guidance,Control and Dynamics, 1984, 7(5):596-602

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