Cooperative control for target search, classification and attack for AUAVs(attack uninhabited air vehicles)

The purpose of this research is to investigate the effectiveness of a team of AUAVs in various scenarios using cooperative behavior algorithms. The search-theoretic approach based on "rate of return" maps is developed to get the cooperative search strategy that guides the movement of a group of AUAVs so as to get as close to optimal non-implementable search plan as possible. Templates are developed and views are combined to maximize the probability of correct target classification over various aspect angles. A false classification matrix is used to represent the probability of incorrectly classifying nontargets as target. Monte Carle simulation runs for each scenario to evaluate the cooperative control strategy relative to the non-cooperative cases. Simulation results shows that cooperative behavior has significantly decreased the number of False Target Attack(FTA) with almost 100%, and cooperative control allows for near optimal solution of the correlative behavior of a group of AUAVs in battle field.