Journal of Korean Society for Quality Management (품질경영학회지)

Korean Society for Quality Management (한국품질경영학회)
권호 표지
DOI QR코드

DOI QR Code

A Study on the Performance Improvement of Position Estimation using the Multi-Sensor Fusion in a Combat Vehicle

다중센서 융합을 통한 전투차량의 위치추정 성능 개선에 관한 연구

  • Nam, Yoonwook (3rd Land Systems Team, Defense Agency for Technology and Quality) ;
  • Kim, Sungho (Electronics Research Team, HYUNDAI ROTEM COMPANY) ;
  • Kim, Kitae (1st Navigation Development Team, Hanwha Corporation) ;
  • Kim, Hyoung-Nam (Department of Electronics Engineering, Pusan National University)
  • 남윤욱 (국방기술품질원 기동화력3팀) ;
  • 김성호 (현대로템주식회사 전자연구팀) ;
  • 김기태 ((주)한화 항법개발1팀) ;
  • 김형남 (부산대학교 전자공학과)
  • Received : 2020.08.31
  • Accepted : 2020.12.17
  • Published : 2021.03.31
Download PDF
⟨ Previous Next ⟩

Abstract

Purpose: The purpose of this study was to propose a sensor fusion algorithm that integrates vehicle motion sensor(VMS) into the hybrid navigation system. Methods: How to evaluate the navigation performance was comparison test with the hybrid navigation system and the sensor fusion method. Results: The results of this study are as follows. It was found that the effects of the sensor fusion method and α value estimation were significant. Applying these greatly improves the navigation performance. Conclusion: For improving the reliability of navigation system, the sensor fusion method shows that the proposed method improves the navigation performance in a combat vehicle.

Keywords

References

  1. B. H. Shim, H. J. Jo, and J. E. Kim. 2015. A Study on Dependency Tracking Target Aiming Systems Improvement of the Naval Electro Optical Tracking Systems. Journal of the Institute of Electronics and Information Engineers 52(9):125-131. https://doi.org/10.5573/IEIE.2015.52.9.125
  2. D. H. Hyun and H. B. Yoon. 2009. Robust Maneuvering Target Tracking Applying the Concept of Multiple Model Filter and the Fusion of Multi-Sensor. Journal of Intelligent Information System 16(1):51-64.
  3. H. S. Yu, C. J. Kim, K. J. Yoo, and Y. S. Lee, H. W. Park. 2011. An Attitude Error Estimation Performance Comparison of Tightly Coupled INS/GPS Navigation System using Different Measurements. Journal of the KIMST 14(1):49-54.
  4. H. S. Yu, T. H. Kim, C. J. Kim, Y. S. Lee, and H. W. Park. 2012. A Study on Methods of Measuring and Compensating Misalignment between Inertial Sensor Body and Housing Frame. Journal of the KIMST 15(4):374-380.
  5. K. S. Lee and H. B. Yoon. 2011. Improvement of Position Estimation Based on the Multi-sensor Fusion in Underwater Unmanned Vehicles. International Journal of Fuzzy Logic and Intelligent Systems 21(2):178-185.
  6. S. H. Kim, G. K. Kim, H. K. Kwon, and S. J. Yu, B. H. Park, B. G. Lee, E. H. Kim. 2016. A Study on Measurement of Gun's Attitude of K2 MBT Using Inertial Navigation System and Its Effects on the Hit Probability. Journal of the KIMST 19(2):218-226
  7. S. Y. Cho, Munkhzul, E., and K. H. Kim. 2013. Modified UKF Considering Real-Time Implementation of the Multi-Rate INS/GPS Integrated Navigation System. Journal of Institute of Control, Robotics and Systems 19(2):87-94. https://doi.org/10.5302/J.ICROS.2013.19.2.087
  8. T. S. Yoo, G. P. Chung, and S. I. Yoon. 2013. Development of Integrated Navigation Algorithm for Underwater Vehicle using Velocity Filter. Journal of Ocean Engineering and Technology 27(2):93-99. https://doi.org/10.5574/KSOE.2013.27.2.093
  9. Y. B. Park. 2009. Design and Performance Analysis of NHC/ZUPT Kalman Filter with Mounting Misalignment Estimation. Journal of the KIMST 12(5):636-643.
  10. Y. W. Nam. 2019. Performance Analysis of Precise Positioning for the Combat Vehicle using the Stand-alone GPS. Journal of the Korean Society of Mechanical Technology 21(1):56-62. https://doi.org/10.17958/ksmt.21.1.201902.56
  11. Y. H. Kim, J. J. Hur, and G. S. Kim, 1994, Development of the Statistical Process Control System Using the Kalman Filter. Journal of Korean Society for Quality Management 22(2):20-32.