[1]房建成,王庆,吴秋平,等.改进的车载DR系统自适应扩展卡尔曼滤波模型及仿真研究[J].东南大学学报(自然科学版),1999,29(1):35-39.[doi:10.3969/j.issn.1001-0505.1999.01.007]
 Fang Jiancheng,Wang Qing,Wu Qiuping,et al.A New Modified Adaptive Extended Kalman Filter of DR System for Land Vehicle Navigation[J].Journal of Southeast University (Natural Science Edition),1999,29(1):35-39.[doi:10.3969/j.issn.1001-0505.1999.01.007]
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改进的车载DR系统自适应扩展卡尔曼滤波模型及仿真研究()
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《东南大学学报(自然科学版)》[ISSN:1001-0505/CN:32-1178/N]

卷:
29
期数:
1999年第1期
页码:
35-39
栏目:
仪器科学与技术
出版日期:
1999-01-20

文章信息/Info

Title:
A New Modified Adaptive Extended Kalman Filter of DR System for Land Vehicle Navigation
作者:
房建成1 王庆2 吴秋平2 万德钧2
1 北京航空航天大学第五研究室, 北京 100083)(2 东南大学仪器科学与工程系, 南京 210096
Author(s):
Fang Jiancheng1 Wang Qing2 Wu Qiuping2 Wan Dejun2
1 Beijing University of Aeronautics and Astronautics, Beijing 100083
2 Department of Instrument Science and Engineering, Southeast University, Nanjing 210096
关键词:
陆地导航 航位推算 卡尔曼滤波 自适应算法
Keywords:
land navigation dead reckoning Kalman filtering adaptive algorithm
分类号:
U666.12
DOI:
10.3969/j.issn.1001-0505.1999.01.007
摘要:
提出了车载DR系统改进的自适应扩展卡尔曼滤波模型及其滤波算法. 由于考虑了速率陀螺漂移误差中的马尔柯夫过程成分,和采用描述机动载体运动的“当前”统计模型及自适应算法,提高了DR系统模型的准确性. 计算机仿真结果表明,应用该模型和算法与改进前相比,DR系统的定位精度得到明显提高.
Abstract:
A modified adaptive extended Kalman filter and filtering algorithm of dead reckoning (DR) system for land vehicle navigation are proposed. Because of consideration of Markov process component in random drifts of rate gyro, and application of a current statistical model and adaptive algorithm for estimating maneuvering vehicles, the accuracy of the DR system model is greatly enhanced. The computer simulation results show that the positioning accuracy of the DR system can be greatly improved by means of this filter and adaptive algorithm.

参考文献/References:

[1] 房建成,申功勋.车载DR系统自适应扩展卡尔曼滤波模型的建立及仿真研究.中国惯性技术学报,1998,6(3):24~28
[2] 房建成,万德钧.GPS组合导航系统在车辆导航中的应用.东南大学学报,1996,26(3):96~102
[3] Zhou H R,Kumar K S P.A current statistical model and adaptive algorithm for estimating maneuvering targets.AIAA,Journal of Guidance,Control and Dynamics,1984,7(5):596~602
[4] Krakiwsky E J,Harris C B,Wong R V C.A Kalman filter for integrated of dead reckoning,map matching,and GPS positioning.In:Proceedings of IEEE Position Location and Navigation Symposium.Orlando,Florida,1988.39~46
[5] Poppen R F,Mathis D L.Integrated of GPS with dead reckoning and map matching for vehicular navigation.In:Proceedings of the 1993 National Technical Meeting of the Institute of Navigation.San Francisco,CA,America,1993.158~164
[6] Kao W W.Integration of GPS and dead reckoning navigation system.In:Proceedings of VNIS’91,Dearborn,Michigan,America,1991.635~643
[7] Ramjattan A N,Gross P A.A Kalman filter model for an integrated land vehicle navigation system.Journal of Navigation,1995,48(2):293~302
[8] 房建成,申功勋,万德钧等.GPS/DR组合导航系统自适应扩展卡尔曼滤波模型的建立.控制理论与应用,1998,15(3):385~390

相似文献/References:

[1]吴秋平,万德钧,徐晓苏,等.车载GPS/DR组合导航系统的研究及其滤波算法[J].东南大学学报(自然科学版),1997,27(2):55.[doi:10.3969/j.issn.1001-0505.1997.02.010]
 Wu Qiuping,Wan Dejun,Xu Xiaosu,et al.Design of GPS/DR Integrated Navigation System for Vehicle and Filter Algorithm[J].Journal of Southeast University (Natural Science Edition),1997,27(1):55.[doi:10.3969/j.issn.1001-0505.1997.02.010]

备注/Memo

备注/Memo:
基金项目: 中国船舶总公司“八五”预研项目及江苏省应用基础研究基金资助项目(BJ95026).
第一作者:男,1965年生,博士后.
更新日期/Last Update: 1999-01-20