Method for Target Grouping Based on CFSFDP Algorithm

Situation assessment perceives the information of battlefield targets, infers the intention of enemy, and aids the command staff to make correct decisions. However, there are so many targets in the modern war, and it leads plenty of information which makes situation assessment more difficult. Target grouping divides large amounts of battlefield targets into several space groups and decreases information quantity. In this way, the difficulty of situation assessment is reduced, and the efficiency of decision is increased. In order to solve the target grouping, this paper proposes a target grouping method based on Clustering by Fast Search and Find of Density Peaks algorithm. Regarding targets grouping as dataset clustering, this method searches the clustering centers and classifies other data points by CFSFDP. Simulation experiment clusters artificial and UCI datasets, and groups the battlefield targets. The result shows that the method proposed in this paper is correct and effective.