Statistical Methods For Classification Of Unmanned Aerial Vehicles

When making decisions regarding multiple objects, researchers often face the problem of choosing the appropriate method for grouping objects with similar characteristics [1]. The present article proposes the use of agglomeration methods to search for links between individual unmanned aerial vehicles (UAVs). An undoubted advantage of the application of agglomeration methods is the possibility of searching for similarities even between many objects to describe which numerous characteristics can be used. The aim of this article is to investigate interrelations between the selected UAVs. For the study purposes the cluster analysis was employed comprising algorithms for grouping objects so that the degree of linkage between elements from the same group was as high as possible, while with elements from the other groups as low as possible. Identification of similar objects, merging them into homogeneous groups, gives the opportunity to organize and classify them.