To address the problem of area coverage search for UAV swarms in unknown environments, a layered pooling map (LPM) model-based area coverage search algorithm for UAV swarms is proposed. Firstly, an environmental map is constructed to represent the task area to be searched. Secondly, by combining pooling techniques from the field of image processing with regional grid maps, a multi-level pooling map model with different resolutions is constructed. Then, a decision objective function including coverage, boundary constraints, and macro benefits is designed, and a distributed information interaction mechanism for UAV swarms suitable for strongly adversarial environments is proposed. Finally, numerical simulations are conducted to verify the effectiveness of the proposed method. The simulation results show that the proposed algorithm can effectively guide the UAV swarm to conduct coverage searches in unknown task areas under different channel quality conditions. In a given coverage search scenario, the algorithm's decision time and coverage are better than other existing methods.