Abstract:

This paper presents a multiple unmanned combat air vehicle (UCAV) cooperative jamming air combat decision-making (MUCJAD) problem. An optimal model is constructed for the MUCJAD on the metric methods of the jamming effect evaluating indexes. In order to solve the model effectively, a heuristic self-adaptive discrete differential evolution (H-SDDE) algorithm is proposed in which, a strategy candidate pool which including four candidate solution generating strategies is designed and two self-adaptive learning processes are introduced for candidate solution generating strategy and its parameters. Furthermore, a threat degree based extensional integer coding scheme, a heuristic individual adjust operator and a constraints satisfaction based individual repair process are designed according to the real-word application. Simulation experiments are conducted on twelve test instances. The results indicate that the H-SDDE algorithm is better than other algorithms in terms of convergence speed and solution quality. The H-SDDE algorithm can enhance the effect of multiple UCAV cooperative jamming.

Key words: unmanned aerial vehicles, cooperative jamming, decision making, heuristic algorithm, self-adaption, optimization, differential evolution