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On the Korean Peninsula, many field-artillery units of the Republic of Korea and the Democratic People’s Republic of Korea confront each other on opposite sides of the border. An artillery counter-fire engagement between the two sides is a realistic scenario. A commander of a field artillery unit must decide quite often when to move and/or when and where to fire. Typically, such decisions depend on the commander’s intuition and experience without any formal analysis. This may lead to wrong tactical decisions. Thus, there is need for reliable battlefield analysis based on data such as unit size, the capability of intelligence-gathering and targeting assets, and the precision and lethality of fire. The main purpose of this thesis is to develop analytical models for counterfire warfare of field artillery using stochastic duels. We develop discrete-time Markov chain and continuous-time Markov chain models and apply them to study the effect of defensive and offensive scooting on the outcome of the exchange under various operational assumptions. The models, and the analyses they facilitate, can aid artillery field-commanders in making better, more informed, tactical decisions on the battlefield, in accordance with the given scenario. Our analytical models can be one component in the process in which the artillery develops its capability and effectiveness operationally and tactically. Dae-wi, Republic of Korea Army Approved for public release. Distribution is unlimited. |
