Distributed cooperative jamming task allocation algorithm based on improved multi-pheromone ant colony algorithm

In order to solve the problem of distributed cooperative jamming task allocation of UAV swarm, an optimal allocation method based on improving the cover efficiency of manned aircraft is proposed. Firstly, based on the cooperative interference of multiple UAVs, a model of common detection exposure area of networked radar is established.Then, according to the concept of safety zone in the jamming effectiveness evaluation criterion, a more objective and comprehensive jamming evaluation function model is established by combining the shortest distance between the manned aircraft and the exposed area boundary, the feasible area range for the manned aircraft to plan the safe track in the next step and the degree of suppression of the radar exposed area. Finally, based on the multi-pheromone ant colony algorithm, the adjustment and improvement are made to adjust the pheromone learning rate and path planning strategy more intelligently, improve the model optimization rate and optimization ability, and give the specific implementation logic. Through simulation, it is found that this method has more stable and fast convergence ability than traditional genetic algorithm, and has stronger global optimization ability than traditional ant colony algorithm. Especially With the expansion of operation scale, the convergence performance of the algorithm is more prominent, and it has better real-time operation and can be closer to practical application.