Date of Award

Summer 2017

Document Type

Thesis

Degree Name

Master of Science (MS)

Department

Computational Modeling & Simulation Engineering

Program/Concentration

Modeling and Simulation

Committee Director

Masha Sosonkina

Committee Member

Saikou Diallo

Committee Member

Yuzhong Shen

Abstract

The United States Air Force AC-130 gunships have been in operation since the Vietnam War and have seen frequent use during recent conflicts. They are able to employ gun weapon systems from above a target in a way that maximizes possible time on target. When firing, the gun operators must deal with miss distances caused by winds acting on the projectile in flight. Operators currently perform a “tweak” to predict a ballistic wind affecting fired rounds which is then used in the fire-control to correct for the real winds and bring shots onto target. This correction, a single-point wind prediction, is made using only the initial state of the gun and aircraft and the final impact location. This thesis explores the possibility of using a round tracking sensor to track a projectile as it falls and produce a multipoint ballistic wind which would be better at correcting for true winds than a single-point ballistic wind.

An algorithm for a multipoint wind prediction method is described and simulation are run using it and a single-point prediction method against measured wind profiles. The results of the single-point and multipoint ballistic winds are compared to the measured winds to test for a goodness of fit. The results are also tested for stability that when used the ballistic wind remains valid even if the aircraft and gun change state from the initial state when the ballistic wind was predicted. The results show that a multipoint ballistic wind that is a better fit and more stable ballistic wind than a single-point ballistic wind is possible using the algorithm presented. Also, the multipoint ballistic wind can be produced with very few data points along the trajectory of the projectile.

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DOI

10.25777/h8yz-9d19

ISBN

9780355316636

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