车载GPS/DR组合导航系统的数据融合算法

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

北京航空航天大学电子工程系

基金项目: 国家重点科技攻关计划资助项目(9613020502)

详细信息

作者简介:
寇艳红(1969-),女,河南许昌人,讲师,100083,北京.

中图分类号: TN 967.2; U 491.512
计量
- 文章访问数: 2876
- HTML全文浏览量: 57
- PDF下载量: 1205
- 被引次数: 0
出版历程
- 收稿日期: 2001-10-19
- 网络出版日期: 2003-03-31

Data Fusion Algorithm for GPS/DR Integrated Vehicle Navigation System

Dept. of Electronic Engineering, Beijing University of Aeronautics and Astronautics

摘要

摘要: 建立了车载GPS/DR(全球定位系统/航位推算)组合导航系统自适应联合Kalman滤波的数学模型,研究了综合运用子系统状态评估、自适应信息分配、误差补偿、迭代扩展Kalman滤波、抗野值干扰、U-D协方差分解滤波等技术来提高精度和可靠性的融合滤波算法;针对滤波发散的问题,引入了一种在线估计观测噪声统计特性的自适应滤波方法.理论分析和半物理仿真结果表明,所设计的算法在精度、可靠性、适应性、实时性等方面效果都很好.
- 卡尔曼滤波 /
- 自适应滤波 /
- 组合导航 /
- 数据融合 /
- 航位推算法 /
- GPS
Abstract: An adaptive federated Kalman filter model for GPS/DR integrated vehicle navigation system was established. Attention was focused on the filter algorithm. To improve the precision and reliability, data fusion techniques such as subsystem state evaluation, adaptive information distribution, error compensation, iterative extended Kalman filter, resist outliers, and U-D covariance decompose were used in the algorithm. To solve the problem of filtering divergence, a method to estimate the statistical feature of measurement noise was introduced. Theoretical analysis and semi-physical simulation results demonstrated that the algorithm is efficient in precision, reliability, adaptivity and real-time processing rate.
- Kalman filtering /
- adaptive filtering /
- integrated navigation /
- data fusion /
- dead reckoning /
- GPS

HTML全文

参考文献(1)

[1] Krakiwsky E J, Harris C B, Wong R V C. A Kalman filter for integrated of dead reckoning, map matching and GPS positioning . In:Institute of Navigation, ed. IEEE PLANS'88 . Orlando:Institute of Navigation,1988. 39~46 [2] Eduardo M N, Hugh D W. A high integrity navigation architecture for outdoor autonomous vehicles[J]. Robotics and Autonomous Systems,1999,26(2):81~97 [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 . 遥测遥控,2002,23(1):7~12 Kou Y H,Zhang Q S,Li X L. 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] 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 [5] 常青. GPS定位方法及其应用研究 . 北京:北京航空航天大学电子工程系,1998 Chang Q. Study on GPS positioning method and its application . Beijing:Dept. of Electronic Engineering, Beijing University of Aeronautics and Astronautics,1998(in Chinese) [6] 彭飞. 智能车辆定位与导航系统研究 . 北京:北京航空航天大学电子工程系,2000 Peng F. The study on intelligent vehicle location and navigation system . Beijing:Dept. of Electronic Engineering, Beijing University of Aeronautics and Astronautics,2000(in Chinese) [7] 胡峰,孙国基. Kalman滤波的抗野值修正[J]. 自动化学报,1999, 25(5):692~696 Hu F,Sun G J. Fault-tolerant improvemnet on Kalman filter [J]. Acta Automatica Sinica,1999, 25(5):692~696(in Chinese) [8] 高钟毓. 工程系统中的随机过程—随机系统分析与最优滤波[M]. 北京:清华大学出版社,1998 Gao Z Y. Stochastic process in engineering system—stochastic system analysis and optimal filtering[M]. Beijing:Tsinghua University Press,1998(in Chinese) [9] Sage A P, Husa G W. Adaptive filtering with unknown prior statistics . In:Proceedings of Joint Automatic Control Conference . Boulder Colorado,1969. 760~769 [10] 张常云. 自适应滤波方法研究[J]. 航空学报, 1998, 19(7):96~99 Zhang C Y. Approach to adaptive filtering algorithm [J]. Acta Aeronautica Et Astronautica Sinica, 1998, 19(7):96~99(in Chinese) [11] 宋文尧,张牙. Kalman滤波[M]. 北京:科学出版社, 1991 Song W Y,Zhang Y. Kalman filtering[M]. Beijing:Science Press, 1991(in Chinese)

施引文献

资源附件(0)

访问统计