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Effective target assignment plays a crucial role in maximizing the efficiency and success of cooperative air combat involving multiple UAVs in complex and dynamic environments. Accurate target threat assessment is essential for successful target assignment. This study proposes a threat assessment method that considers multiple threat factors of UAV targets and introduces an uncertain information representation technique using interval-valued intuitionistic fuzzy number. To achieve the fusion of multi-moment target information, weights are assigned to the time series using the normal distribution method. Furthermore, a weight optimization model is presented to integrate the threat factor weights obtained through the AHP method and the entropy method. For solving the multi-weapon multi-target assignment problem, a target assignment method based on the VNS-IBPSO algorithm is introduced. This method improves upon the limitations of the BPSO algorithm, such as limited local search capability and premature convergence, by combining variable neighborhood search (VNS) and an improved binary particle swarm optimization algorithm (IBPSO). The effectiveness of the proposed method is validated through simulation experiments, which demonstrate its ability to quickly and accurately complete target assignment tasks. This method provides an effective solution for the coordination task allocation of multi-UAV cooperative air combat.