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http://dx.doi.org/10.9766/KIMST.2016.19.2.177

Recursive Bayesian Filter based Strike Velocity Estimation for Small Caliber Projectile  

Kim, Jong-Hwan (Department of Mechanical & Systems Engineering, Korea Military Academy)
Jo, Seungsik (Department of Mechanical & Systems Engineering, Korea Military Academy)
Publication Information
Journal of the Korea Institute of Military Science and Technology / v.19, no.2, 2016 , pp. 177-184 More about this Journal
Abstract
This paper presents a strike velocity estimation using the recursive Bayesian filter that operates both correction and prediction models to probabilistically remove noises of sensors and accurately estimate the strike velocity during the real-time experiments. Four different types of bullets such as 5.56 mm M193, 7.62 mm M80, 5.45 mm 7N10 and 7.62 mm MSC were used to validate the proposed method. Compared to the existing method, the proposed method statistically results in higher stability of the strike velocity estimation as well as its reliability for the ballistic limit velocity computation.
Keywords
Ballistic Limit Velocity; Strike Velocity; Live Bullet Experiment; Recursive Bayesian Filter; Velocity Estimation;
Citations & Related Records
Times Cited By KSCI : 1  (Citation Analysis)
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