Research on Multi-target Attack Scheme Based on K-means Clustering Algorithm

The current battlefield environment is complex, with numerous and unevenly distributed targets in the attack area. It is difficult for commanders to make accurate real-time choices on the minimum amount of bombs to be dropped and the location of attack points. This article is based on the K-means clustering algorithm and analyzes multiple randomly distributed targets in the attack zone for two different combat situations. Mathematical models are established and corresponding attack schemes are studied. The experimental results show that the attack scheme proposed in this article can optimize the number of bombs dropped and provide accurate location information of each attack point, ultimately providing reliable attack schemes for commanders.