# Clustering Method of Large-Scale Battlefield Airspace Based on Multi A * in Airspace Grid System
## 5 Experimental Simulation and Analysis
### Evaluation of Airspace Clustering Effect
#### 5.2.2 Experimental Results and Analysis  
Simulation 1: Take the airspace parameter planning set in Section 4.1 as the task scenario, obtain the initial parameter airspace total quantity \(N=15\) of experimental simulation 1, and set the airspace target cluster quantity \(M=6\). Observe the change of airspace conflict detection results by changing the airspace safety margin distance. The experimental results are shown in the Figures 21 and 22. From the experimental results of simulation 1, it can be found that in the whole experiment process, the safety margin distance between airspace has been adjusted for 10 times, and the corresponding detection result parameters have been adjusted for each time. In terms of the accuracy of detection results, 8 of the 10 detection results are accurate, of which two detection results have errors; the error values are 1 and 2. It shows that the accuracy of detection results of airspace conflict detection based on airspace clustering is different from that of traditional wide area airspace conflict detection. The main reason is that there may be some fuzzy disputed airspace near the edge cluster lines, which leads to the overall detection of multiple detections or missing detections. In terms of detection speed ratio, the speed obtained from simulation 1 is always lower than the same speed reference line (\(y=1\)) set in advance since the first detection, and the detection efficiency is improved by 1.6-10.9%. It shows that clustering the whole task airspace can improve the speed of conflict detection and improve the efficiency of airspace conflict detection. Simulation 2: Keep the total number \(N\) of airspace and the safety margin distance \(R\) between airspace unchanged, adjust the number \(M\) of target airspace clusters, detect airspace conflicts in the whole task airspace, and obtain the corresponding result parameters. After clustering, airspace conflict detection is carried out in each cluster according to the  
From the experimental results of simulation 2, it can be found that the number of target airspace clusters has been adjusted for 10 times in the whole experiment process, and the corresponding detection result parameters have been adjusted for each time. In terms of the accuracy of detection results, 8 of the 10 detection results are accurate, of which two detection results have errors; the error values are 2 and 1. It shows that the accuracy of detection results of airspace conflict detection based on airspace clustering is different from that of traditional wide area airspace conflict detection. The main reason is that there may be some fuzzy disputed airspace near the edge cluster lines, which leads to the overall detection of multiple detections or missing detections. In terms of detection speed ratio, the speed obtained from simulation 2 is always lower than the same speed reference line (\(y=1\)) set in advance since the first detection, and the detection efficiency is improved by 1.6-6.2%. It shows that the efficiency of conflict detection speed is improved by clustering the whole task airspace. At the same time, it is observed that with the increase of the number of target airspace clusters, the time consumed for airspace conflict detection based on airspace clustering is gradually reduced, and finally tends to a fixed constant that does not change. The factor of the change in the exploration constraint detection time should be the number of airspace. Clustering is carried out in a limited number of airspace. When the number of airspace clusters increases to a certain level, due to the limited number of airspace clusters, the airspace clustering has reached saturation, and the clustering results will no longer increase with the set number of airspace clusters, so the detection time will not change.