A cooperative search method of multiple AUV (autonomous underwater vehicle) on the basis of improved BSO (brain storm optimization) algorithm was proposed to search underwater moving targets. The target motion was predicted on the basis of Markov process, both the detection information and prediction information were used to update the target existence probability. AUVs shared the target existence probability, environmental uncertainty, and the coordination of pheromones, then planed the search path by rolling optimization strategy. The effectiveness and robustness of the proposed method were verified by simulation. The simulation results show that the method can search moving targets under different motion patterns, the search effect is better than the random algorithm, traversal algorithm and BSO algorithm, it is not sensitive to different initial departure positions of AUVs, improving the flexibility of tactical use.