Browse > Article
http://dx.doi.org/10.9766/KIMST.2020.23.1.018

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

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)
Publication Information
Journal of the Korea Institute of Military Science and Technology / v.23, no.1, 2020 , pp. 18-27 More about this Journal
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
Launch Point Estimation; High Speed Vehicle; Interacting Multiple Model; Ballistic Coefficient; Thrust;
Citations & Related Records
연도 인용수 순위
  • Reference
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.   DOI
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.   DOI
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.   DOI
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.   DOI
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.   DOI