Aiming at the problems that the intelligent deployment method of air defense formations cannot take into account both regional cover and target cover at the same time, the artificially formulated complex rules are difficult to solve, and the algorithm execution efficiency is low, an air defense formation deployment method based on Independent Multi-Agent Proximal Policy Optimization (IN-MAPPO) is proposed. An independent actor-critic network is designed to adapt to the different roles of fire units. It promotes the collaborative cooperation of fire units to complete hybrid deployment tasks through centralized value functions and reward functions, and improves the resistance capability and the overall deployment performance of the formation. Experimental results show that IN-MAPPO can complete the mixed deployment tasks according to the role of the agent, improve the resistance capability of remote fire units, and reduce the training time by 13.7% compared with other MAPPO algorithms. Compared with existing intelligent algorithms, the coverage area of fire units is increased by 4.2%, the effective cover width is increased by 12.3%, and the execution efficiency of the algorithm increased by 95.9%.