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Increasing Air Defense Capability By Optimizing Burst DistanceTurkuzan, Mehmet 01 December 2010 (has links) (PDF)
In this thesis, burst distance is optimized to increase air defense capability for systems utilizing airburst munitions. A simulator program is created to use during the study by taking advantage of the MATLAB environment. While creating the simulator program, a munition path model is derived by using fourth order Runge-Kutta method. Then, simulations are conducted at different burst distances and related information are recorded. By using least square optimization method and gathered data, optimum burst distance is found. Moreover, the effects of several factors on optimum burst distances are analyzed, including: the weights of the objectives in the optimization, target dimensions, target range, wind, target position ambiguity, firing angle, and velocity ambiguity after burst. Furthermore, a firing method is proposed. The result of the proposed firing method and the optimum solution are compared and success is presented. To sum up, this study presents a way to find optimum burst distance, analyzes the factors that may affect optimum burst distance, and suggests a firing method for effective shots.
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An Effectiveness Evaluation Method For Airburst ProjectilesSaygin, Oktay 01 May 2011 (has links) (PDF)
Airburst projectiles increase the effectiveness of air defense, by forming clouds of small pellets. In this work, in order to evaluate the effectiveness of airburst projectiles, Single Shot Kill Probability (SSKP) is computed at different burst distances by using three lethality functions defined from different measures of effectiveness. These different measures are target coverage, number of sub-projectile hits on the target and kinetic energy of sub-projectiles after burst. Computations are carried out for two different sub-projectile distribution patterns, namely circular and ring patterns. In this work, for the determination of miss distance, a Monte Carlo simulation is implemented, which uses Modified Point Mass Model (MPMM) trajectory equations. According to the results obtained two different distribution patterns are compared in terms of effectiveness and optimum burst distance of each distribution pattern is determined at different ranges.
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