Situation awareness is an important factor in the effectiveness of aerial missions. One of the major problems with the UAV is that human operators lack situation awareness. Limited bandwidth does not allow telepresence to a degree, which gives the same level of situation awareness that pilots of regular airplanes have. The best solution would be to equip UAV with a “situation awareness” system that in the real time provides operators with the information necessary for effective mission control and decision making, and allows effective supervisory control of the UAV. Vision in advanced creatures is a component of situation awareness, navigation and planning systems. Fast information processing and decision making requires reduction of informational and computational complexities. The brain achieves this goal using implicit symbolic coding, hierarchical compression, and selective processing of visual information. The Network-Symbolic representation, in which both systematic structural/logical methods and neural/statistical methods are the parts of a single mechanism, converts visual information into relational Network-Symbolic knowledge models, effectively resolving ambiguity and uncertainty in the visual information, and avoiding artificial precise computations of 3-dimensional models. The UAV equipped with such smart vision, will have a situation awareness system that gives operators better control over aircraft and significantly improves surveillance and reconnaissance capabilities.