Decision Making under Uncertainty

The objectives of our Phase I effort are to characterize target sensor measurement uncertainties and feature extraction uncertainties; determine how and where, in the processing chain, these affect target discrimination and classification; show how the different sources of uncertainty lead to the cumulative uncertainty in the final decision; provide techniques that will be instrumental to optimizing the design of sensor architectures in order to minimize the effects of uncertainty; and demonstrate that our approach is an effective and efficient solution to determining what measurements and/or tracks should be exchanged between platforms in order to achieve a robust decision. Approved for Public Release 14-MDA-7979 (16 September14).