Abstract
Projectiles are solid projectiles fired from firearms or air rifles, made of metal, generally from lead. The caliber of the projectile is 12.7 x 99 mm. In the projectile motion, to achieve the target, we need to estimate the motion by using some estimation methods. In this paper, the estimation of projectile of caliber 12.7 x 99 mm motion is using Ensemble Kalman Filter (EnKF) method. In simulations, we compare EnKF and KF method. The projectile dynamics model is a non-linear system. The EnKF method can be applied for the non-linear system and KF method for the nonlinear system is approximated to the linearized model before applying the KF algorithm. The final result of this paper shows that Ensemble Kalman Filter (EnKF) is better to estimate the model of projectile motion with the error estimation of EnKF is 23.5% smaller in x-position, 58.8% smaller in h-position, 16.2 % smaller in ν-position, 77.8 % smaller in angle and the computation of time is 3.85 % faster than the estimation results using KF method.
Original language | English |
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Pages (from-to) | 163-173 |
Number of pages | 11 |
Journal | Procedia Computer Science |
Volume | 144 |
DOIs | |
Publication status | Published - 2018 |
Event | 3rd International Neural Network Society Conference on Big Data and Deep Learning, INNS BDDL 2018 - Sanur, Bali, Indonesia Duration: 17 Apr 2018 → 19 Apr 2018 |
Keywords
- Ensemble Kalman Filter (EnKF)
- Kalman Filter (KF)
- Projectile Motion