Hybrid Genetic Particle Swarm Algorithm for Radar Collaborative Interference Allocation

Radar with different parameters will make the threat degree of radar different, interference sources should have a reasonable and perfect jamming strategy when facing cooperative radar. Due to the large number of radar parameters, this paper uses grey correlation method to divide radar parameters into two categories: benefit type and cost type. Jamming allocation strategy is taken as the input of the objective function, and the area of the jamming area that can be detected by the radar is taken as the output, using area size to judge the pros and cons of jamming strategies. In order to improve the precision of radar cooperative interference allocation method, a hybrid genetic particle swarm optimization algorithm is used. Simulation results show that the proposed algorithm is superior to binary particle swarm optimization and genetic algorithm.