Aimed at the problems that detection efficiency is low, and accuracy of conflict detection is not high among a large number of drones in high-density local battlefield airspace in the future, a real-time and rapid detection of conflicts is obtained among a large number of drones in airspace by constructing a drone protection zone model and a battlefield airspace grid model to extract the airspace position matrix for each drone, and by using the Hadamard product calculation method and the properties of composite and prime factor decomposition for drone conflict detection to identify the drone numbers, positions, altitudes, and other information of conflicts. And on the basis of this, operational layers, avoidance layers and collision thresholds are introduced to establish a quantifiable airspace-capacity evaluation framework. The simula tion results indicate that compared to the traditional methods, this Hadamard product calculation method enables the complexity of conflict detection to reduce from O(Cn-2 n ) to level O(n-1), and the conflict de tection time for 800 drones is controlled within 40 ms, greatly improving the efficiency of conflict detec tion. Through further processing of the conflict set under an acceptable collision probability criterion, reli able airspace-capacity values can be worked out, offering theoretical and technical support for the safe and efficient operation of large-scale, high-density drones in local airspace.