Journal of the Korea Institute of Military Science and Technology (한국군사과학기술학회지)

The Korea Institute of Military Science and Technology (한국군사과학기술학회)
권호 표지
DOI QR코드

DOI QR Code

Experiment on Multi-Dimensioned IMM Filter for Estimating the Launch Point of a High-Speed Vehicle

초고속 비행체의 발사원점 추정을 위한 다중 IMM 필터 실험

  • Kim, Yoon-Yeong (Department of Industrial and Systems Engineering, Korea Advanced Institute of Science and Technology) ;
  • Kim, Hyemi (Department of Industrial and Systems Engineering, Korea Advanced Institute of Science and Technology) ;
  • Moon, Il-Chul (Department of Industrial and Systems Engineering, Korea Advanced Institute of Science and Technology)
  • 김윤영 (한국과학기술원 산업 및 시스템 공학과) ;
  • 김혜미 (한국과학기술원 산업 및 시스템 공학과) ;
  • 문일철 (한국과학기술원 산업 및 시스템 공학과)
  • Received : 2019.04.08
  • Accepted : 2020.01.10
  • Published : 2020.02.05
Download PDF
⟨ Previous Next ⟩

Abstract

In order to estimate the launch point of a high-speed vehicle, predicting the various characteristics of the vehicle's movement, such as drag and thrust, must be preceded by the estimation. To predict the various parameters regarding the vehicle's characteristics, we build the IMM filter specialized in predicting the parameters of the post-launch phase based on flight dynamics. Then we estimate the launch point of the high-speed vehicle using Inverse Dynamics. In addition, we assume the arbitrary error level of the radar for accuracy of the prediction. We organize multiple-dimensioned IMM structures, and figure out the optimal value of parameters by comparing the various IMM structures. After deriving the optimal value of parameters, we verify the launch point estimation error under certain error level.

Keywords

References

  1. Naveh, B. Z., & Lorber, A., "Theater Ballistic Missile Defense," Progress in Astronautics and Aeronautics, 192, 1-397, p. 359, 2001.
  2. Lih, Y., Kirubarajan, T., Bar-Shalom, Y., & Yeddanapudi, M., "Trajectory and Launch Point Estimation for Ballistic Missiles from Boost Phase LOS Measurements," IEEE Aerospace Conference. Proceedings, Cat. No. 99TH8403,n Vol. 4, pp. 425-442, 1999.
  3. A. Farina, B. Ristic, D. Benvenuti, "Tracking a Ballistic Target: Comparison of Several Nonlinear Filters," IEEE Transactions on Aerospace and Electronic Systems, 38(3), pp. 854-867, 2002. https://doi.org/10.1109/TAES.2002.1039404
  4. Li, X. R., & Jilkov, V. P., "Survey of Maneuvering Target Tracking. Part I. Dynamic Model," IEEE Transactions on Aerospace and Electronic Systems 39(4), pp. 1333-1364, 2003. https://doi.org/10.1109/TAES.2003.1261132
  5. E. Mazor, A. Averbuch, Y. Bar-Shalom, J. Dayan, "Interacting Multiple Model Methods in Target Tracking: A Survey," IEEE Transactions on Aerospace and Electronic Systems, 34(1), pp. 103-123, 1998. https://doi.org/10.1109/7.640267
  6. R. Kandepu, B. Foss, L. Imsland, "Applying the Unscented Kalman Filter for Nonlinear State Estimation," Journal of Process Control, 18(7), pp. 753-768, 2008. https://doi.org/10.1016/j.jprocont.2007.11.004
  7. Daeipour, E., & Bar-Shalom, Y., "An Interacting Multiple Model Approach for Target Tracking with Glint Noise," IEEE Transactions on Aerospace and Electronic Systems, 31(2), pp. 706-715, 1995. https://doi.org/10.1109/7.381918