Approach for air-to-air confrontment based on uncertain interval information conditions

Model combat information conditions are always uncertain and varied, the uncertain interval theory is therefore introduced into the research of multiple fighters suppressing the integrated air defense system (IADS) problem. Considering that the combat information conditions are uncertain intervals, the payoff function of the game for multiple fighters suppressing the IADS is modeled. Using the operation rules for interval numbers and the possibility degree, an improved chaotic particle swarm optimization (CPSO) is designed to solve the proposed model so as to obtain the optimal game solution. Comparison simulations are performed to analyze the influence of the weapons consumption and the distances of non-escaped zone and jamming on air combat result. Simulation results suggest that Nash equilibrium is achieved and verify the effectiveness of the proposed method.