Cognition-Based Multi-system Radio Fuze Interference Decision

In recent years, with the increasing complexity of the electromagnetic environment, what the jamming equipment has to face is no longer the target of a single system, but a combination of multiple system radio fuzes working together at random, which requires the jamming equipment to have a certain autonomous decision-making ability, and then independently emits the jamming wave pattern for different jamming targets to effectively jamming the targets. In this paper, the wolf pack decision algorithm is used for autonomous decision-making of interference patterns. The main control module plays the role of the head wolf, selects the appropriate jamming strategy according to the target component information received based on sorting and recognition, and assigns the jamming tasks to different jamming modules. The detection module is the detection wolf, detects the interference effect evaluation based on correlation in real time and feeds the evaluation results back to the main control module. And the jamming module is as a fierce wolf, generates the jamming waveform to jamming the target. The multi-system radio fuze interference decision allocation technology based on the wolf pack decision makes use of the existing interference resources automatically complete the optimal allocation of interference patterns and achieve the optimization of jamming effects. The theoretical analysis and simulation show that the jamming strategy allocation for multi-system radio fuze proposed in this paper can realize jamming decision effectively and achieve good interference effects.