Preliminary study on estimation of 12.7 x 99 mm caliber projectile using Unscented Kalman Filter method
Author(s) -
Luh Ayu B.L,
Erna Apriliani,
Hendro Nurhadi
Publication year - 2018
Publication title -
procedia computer science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.334
H-Index - 76
ISSN - 1877-0509
DOI - 10.1016/j.procs.2018.10.518
Subject(s) - projectile , kalman filter , caliber , position (finance) , computer science , extended kalman filter , control theory (sociology) , projectile motion , filter (signal processing) , algorithm , computer vision , artificial intelligence , physics , materials science , control (management) , finance , quantum mechanics , economics , metallurgy
The projectile dynamics model is non-linear system. The specifications of projectile used are 12.7 x 99 mm caliber. In the projectile motion, to achieve the target can be estimated by using some estimation methods. In this study, the estimation of 12.7 x 99 mm caliber projectile motion is computed by using Unscented Kalman Filter (UKF) method. In this simulation, we estimate model of the system by measuring each variables position. The estimation results show the performance of UKF and KF in non-linear systems is different, based on their respective characteristics. The final result of this study shows that the error estimation of UKF is 81 % smaller in x -position, 85 % smaller in h -position and ν-position, 84 % smaller in γ-position. UKF performance is very good for non-linear system and the approach with KF algorithm has less optimal result.
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