Large-scale group target clustering method fusing dynamic values

The invention relates to a large-scale group target clustering method fusing dynamic values, and belongs to the field of large-scale target coverage. According to the method, modeling is carried out on a group composed of a plurality of independent target units, a global value table and a value updating algorithm for all targets in the group are established, information in the global value table is updated in real time through a detection set, and on the basis of the information in the global value table, an improved K-means clustering algorithm is adopted, so that the global value of all targets in the group is obtained. And clustering the large-scale group fused with the dynamic value. The method is based on an improved K-means clustering algorithm, a solution meeting practical requirements is provided for the large-scale group target clustering problem, and the problem that a current method lacks practical operability and target value consideration for the large-scale group target clustering problem is sol