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<p>Reconnaissance missions are not only one of the vital modes of intelligence-gathering  methods; they are one of the most important contributors of military intelligence as well.  They show the battlefield as it is to the commander.  A simplified reconnaissance cycle includes the arrival of reconnaissance requests,  planning of reconnaissance flights, flying the mission and exploitation of the films or  images, and then dissemination of the intelligence reports. The reconnaissance cycle is  modeled for four different scenarios (peace and war as situations, RF-4 and F-16 as  configurations). There are two points of view regarding this cycle. The first is the  reconnaissance requesters' view: they want to know the estimated time it would take for a  request to be answered, based on the resources and other factors, before an actual request  was made. The second is the reconnaissance squadron commanders' perspective: they  want to respond to as many reconnaissance requests as possible. For that reason, they  want to know and revise the ideal numbers of personnel and equipment. For the purpose  of answering these questions, satisfying these requests, and having a better understanding  about the reconnaissance cycle, Reconnaissance Squadron Workflow is modeled,  experimented and analyzed in this thesis.  Analysis includes regression models and partition trees. When results are  considered, we see that there is no common rule to determine which factors (either  decision or noise) are the key determinants for each scenario. But we noticed that noise  factors have much more impact on several measures of effectiveness than decision factors  in each model. Some of these noise factors could be controllable, including aircraft,  camera and pod defect probabilities and their repair times. Therefore, some precautionary  measures should be taken to reduce these defect probabilities and repair times.  Specifically, in the RF-4 configuration models, pilot filming error is a significant  factor, which shows that training of the pilots cannot be ignored. When the F-16 models  are considered, we see that data link defect probability is a significant factor too. This  suggests that special precautions should be taken to keep this capability working.
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<br>Subjects: Modeling; Aerial reconnaissance; Regression analysis</div>
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Kamik, Ernur</div>
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