Uncertainty quantification of a small arms fire control system

A new small caliber fire control system is being designed, and there is interest in understanding how much error can be tolerated in the individual sensors that would still result in acceptable overall performance of the system. State of the art methods in Design of Experiments (DOE)-based surrogate modeling for probabilistic optimization of modeling & simulation were used to characterize the behavior of the system, improve the design based on overall system performance and cost, and predict how uncertainties in the individual sensor performances affected the probability of hit for the weapon system at a given target. A space filling experiment was designed for the projectile trajectory model used to evaluate the system. This model predicts the impact location of an individual round based on the environmental conditions at the time of firing. Using the model, it could be determined what the miss distance would be for the round given differences between what the sensor reads and what the actual conditions are at the time of fire. From the results of the simulations, a surrogate model was fit to the data that predicts the miss distance throughout the entire design space. The surrogate model was used to identify the most influential sensors, and a probabilistic simulation was used to quantify the uncertainty in the system and improve its probability of hit in the most efficient manner. The effort resulted in a recommendation of a design for a reliable, cost effective fire control system.