Each metric was evaluated with initial condition errors and parametric uncertainties of physical constants using linear error theory to validate the use of linear approximations to propagate the errors. The selected metrics are time to roll through bank anglemetric, time-averaged integral of pitch rate metric, and power onset/loss parameter. The robustness of agility metrics has been studied to determine the sensitivity of selected metrics to variations in initial conditions and uncertainties in physical characteristics and coef cients. If in a descending vertical rolling scissors the defender finds himself.
The model can be utilized in the analysis of a single decision situation or as an automated decision making system that selects combat maneuvers in air combat simulators. Otherwisethe fighter with the best sustained rate of climb will have the advantage. The effects of sensor information that will reduce the uncertainty of the model are evaluated using Bayesian reasoning. Sensitivity analysis determines the impacts of different factors on the outcome of the maneuvering decision. Influence diagram analysis produces a probability distribution of the overall utility that represents the successfulness of a maneuver and gives information to make rational maneuvering decisions. In the pilot decision model, the possible combat situations related to each maneuver alternative are associated with a probability and a utility. Unlike most of the existing approaches, an influence diagram graphically describes the factors of a decision process and explicitly handles the decision maker’s preferences under conditions of uncertainty. We simulate and analyze pilot decision making in one-on-one air combat using an influence diagram.
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