Hybrid framework for fusion 2+ in multi-multi air engagement

Fusion 2+ of air-to-air engagement involves pressing, real-time constraints and very large amounts of imperfect data. Real-time data acquired during an air-to-air engagement will have different types of imperfection; two representative classes of imperfection are vagueness and ambiguity in the data. However, the current approaches of managing Fusion 2+ are limited to utilize either vague data or ambiguous data. The most popular fusion technique for vague data is Fuzzy Logic, and for ambiguous data, the Bayesian Network. The challenge addressed in this proposal is to explore the framework of a hybrid processing Fusion 2+ model that can formally process both vague (fuzzy) and ambiguous (probabilistic) data types. There are two major issues for building this Fusion 2+ model. The first issue is to mathematically integrate the heterogeneous models, which have different domains, probability and possibility. The second issue is to programmatically integrate two different S/Ws. For solving the first issue, this research explores and adopts two novel transformation methods between probability and possibility and compares the sensitivity between methods. Also this research provides an Object Oriented Tool for building a hybrid model by adopting an Application Programming Interface, so that we can model the complex (multi-to-multi) Fusion 2+ model of an air-to-air engagement.