Reliability Analysis of the Kalman Filter for INS/GPS Integrated Navigation System Applied to Train

被引:0
|
作者
Cho, Seong Yun [1 ]
Kang, Chang Ho [2 ]
Shin, Kyung Ho [3 ]
机构
[1] Kyungil Univ, Dept Robot Engn, Gyongsan, South Korea
[2] Korea Univ, Res Inst Engn & Technol, Seoul, South Korea
[3] Korea Railrd Res Inst, Railrd Control & Commun Res Team, Uiwang, South Korea
来源
ICINCO: PROCEEDINGS OF THE 16TH INTERNATIONAL CONFERENCE ON INFORMATICS IN CONTROL, AUTOMATION AND ROBOTICS, VOL 2 | 2019年
关键词
INS/GPS; Train Application; Kalman Filter; Observability; RMSE;
D O I
10.5220/0007832602370242
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
This paper aims to analyse the navigation performance that can be provided by the navigation system when applying the INS/GPS integrated navigation system to the train. The performance of the Kalman filter integrating INS and GPS can be summarized by the integrity of the measurement and the observability of the filter. Assuming the integrity of the GPS information used as a measurement is always satisfied, the performance of the filter can eventually be analysed by the observability. The observability of the filter depends on the dynamic trajectory of the train. Because the train has a non-holonomic constraint and onedimensional motion, the filter design and the performance analysis are carried out considering this. We analyse the observability of the filter through simulation and explain the limit of the filter and the flaw of the observability. We also analyse the reliability of the navigation system and present additional research directions.
引用
收藏
页码:237 / 242
页数:6
相关论文
共 50 条
  • [31] Observability analysis of the INS/GPS navigation system on the measurements in land vehicle applications
    Cho, Seong Yun
    Kim, Byung Doo
    Cho, Young Su
    Sik-Choi, Wan
    2007 INTERNATIONAL CONFERENCE ON CONTROL, AUTOMATION AND SYSTEMS, VOLS 1-6, 2007, : 2505 - 2510
  • [32] Integrated Navigation Kalman Filter Design of Spray Robot Based on GPS and Computer Vision
    Guo Guangli
    Mao Xi
    2011 AASRI CONFERENCE ON APPLIED INFORMATION TECHNOLOGY (AASRI-AIT 2011), VOL 1, 2011, : 106 - 109
  • [33] Data Fusion Based on Adaptive Interacting Multiple Model for GPS/INS Integrated Navigation System
    Zhang, Chuang
    Guo, Chen
    Zhang, Daheng
    APPLIED SCIENCES-BASEL, 2018, 8 (09):
  • [34] A Hybrid Method for INS/GPS Integrated Navigation System Based on the Improved Karman Filter and Back Propagation Neural Network
    Hu, Mutian
    Song, Tao
    Ye, Jianchuan
    2024 8TH INTERNATIONAL CONFERENCE ON ROBOTICS, CONTROL AND AUTOMATION, ICRCA 2024, 2024, : 477 - 484
  • [35] Research on Seamless INS/GPS Integrated Navigation Algorithm
    Xu, Tianlai
    Tian, Yang
    MATERIALS AND MANUFACTURING, PTS 1 AND 2, 2011, 299-300 : 1178 - 1181
  • [36] To the Question of the Stability of the Kalman Filter in Integrated Navigation System of Transport Means
    Rastorguev, Vladimir
    2015 17th International Conference on Transparent Optical Networks (ICTON), 2015,
  • [37] The Expanded State Space Kalman filter for GPS navigation
    Yin J.
    Gu M.
    Zhang J.
    Information Technology Journal, 2011, 10 (11) : 2091 - 2097
  • [38] Cubature Kalman filter with closed-loop covariance feedback control for integrated INS/GNSS navigation
    Gao, Bingbing
    Hu, Gaoge
    Zhang, Lei
    Zhong, Yongmin
    Zhu, Xinhe
    CHINESE JOURNAL OF AERONAUTICS, 2023, 36 (05) : 363 - 376
  • [39] Application of the Kalman filtering with BP algorithm in GPS/DRS integrated navigation system
    Zhang Yi-nan
    Fan Yue-zu
    Proceedings of 2004 Chinese Control and Decision Conference, 2004, : 283 - 285
  • [40] A Novel Robust Kalman Filter Algorithm With Unknown Noise Statistics for SINS/GPS Integrated Navigation
    Lai, Xin
    Yang, Fu-Xin
    JOURNAL OF THE CHINESE SOCIETY OF MECHANICAL ENGINEERS, 2023, 44 (01): : 49 - 57