• Journal of the Korea Institute of Military Science and Technology
• /
• v.19 no.2
• /
• pp.177-184
• /
• 2016

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.

• International Journal of Naval Architecture and Ocean Engineering
• /
• v.10 no.6
• /
• pp.762-781
• /
• 2018

This paper presents the ballistic armor performance examination and thickness estimation for the latest naval ship structure materials in the Republic of Korea. Up to date, research regarding methods of ballistic experiments establishing database on the latest hull structure materials as well as a precise method of estimating required thickness of armor against specific projectiles have been rarely researched. In order to build a database and estimate proper thicknesses of structure materials, this study used four structure materials that have been widely applied in naval ships such as AH36 steel, AL5083, AL5086, and Fiber Reinforced Plastics (FRP). A $7.62{\times}39mm$ mild steel core bullet normally fired by AK-47 gun was considered as a threat due to its representativeness. Tate and Alekseevskii's penetration algorithm was also used to calculate a correction factor (${\alpha}$) and then estimate the armor thickness of naval ship hull structure materials with a given impact velocity. Through live fire experiments, the proposed method performance difference was measured to be 0.6% in AH36, 0.4% in AL5083, 0.0% in AL5086, and 8.0% in FRP compared with the experiment results.