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Coordinated Multiple-Target Attack of Multiple UCAVs Using Dynamic Awareness Based on DBN

With new-arriving and updated fusion data, a dynamic awareness model against threats for UCAVs (unmanned combat aerial vehicles) based on dynamic Bayesian network (DBN) is constructed. Using parameters' change in relative DBNpsilas transition, this dynamic awareness model leads to infer the main conditions that can be changed timely in multi-targets attack optimization within complicated aerospace surroundings. In the light of DBNpsilas learning and reasoning algorithms, a coordination planning optimization algorithm for UCAVs is advanced. By means of this DBN awareness model, attack targets re-assignment and cooperative path re-planning for UCAVs may be attained in accordance with given missions and guidelines. Simulations demonstrate that, with the dynamic awareness based on DBN, this autonomous planning method is valid and lays the foundations of a series of complicated missions that may be achieved successfully and autonomously for UCAVs..