In response to the problem of optimizing the deployment of multiple equipment for air defense of key area and anti-unmanned aerial vehicle (UAV) swarm coordination, the effect of air defense elements of key area on the deployment position of equipment is comprehensively analyzed, and the constraints of equipment deployment in the key area are proposed. By combining the factors of target defense fire depth, fire intensity index, fire coverage area and fire interface area, the air defense equipment deployment model is formulated based on the performance of air defense equipment and incomings. A coordinated equipment, multi-protection target air defense method has been established in the strategic strongholds, and the comprehensive protection effectiveness has been enhanced. In addition, an improved Subtraction-Average-Based Optimizer (SABO) algorithm has been proposed, which improves the global search capability by introducing Bernoulli-shifted chaotic mapping, and effectively solves the shortcomings of the basic SABO algorithm such as easy to fall into local optimal solutions. Simulation case studies show that the improved SABO algorithm has obvious advantages in fast convergence as well as global optimization search for the problem of uneven deployment of anti-UAV cluster equipment.