Air target clustering method

Abstract

The invention discloses an air target clustering method which comprises the following steps: S1, based on a comprehensive weighting theory, combining subjective and objective weights of attributes to generate an attribute comprehensive weight influencing a target grouping result; S2, considering the difference of the influence of different attributes on clustering, introducing a comprehensive weight into similarity calculation, optimizing similarity measurement, and constructing an SWBWP index used for determining the optimal clustering number of the target group and a model used for determining the optimal clustering number copt; s3, roughly searching a value interval [Pmin, Pmax] of the deviation parameter P by adopting a half-division method, if all P(i), i=1, 2,..., c<max>-1 corresponding to the clustering number [2, cmax] are searched, calculating SWBWP indexes corresponding to different clustering numbers, and determining an optimal clustering number copt by using the SWBWP indexes; and S4, taking the SWBWP value of the clustering result as a fitness function value, finely searching a deviation parameter subspace [Pn, Px] by adopting an ABC algorithm, and determining an optimal deviation parameter Pb. According to the method, for the target grouping problem with the unknown target group number, the purpose of efficient and accurate target grouping in the aerial high-confrontation environment can be achieved.

Description

technical field [0001] The invention relates to the technical field of decision-making assistance, in particular to an air target clustering method. Background technique [0002] In recent years, with the increasing complexity and abruptness of air confrontation, the group confrontation method will become an important form of air confrontation in the future. The targets in the same confrontation group have a common overall goal. To achieve this goal, the opposing commander will divide the air targets in the group into multiple groups of different sizes, and each group can achieve one of the overall goals. Sub-targets; each group is composed of multiple cooperative formations, and each formation performs specific combat tasks; the formation is composed of more than one air target, and the targets in the formation need to maintain a certain height and distance difference when flying , therefore, targets in the same formation have similar maneuvering states. [0003] Accordin...

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Problems solved by technology

[0005] The above methods are all based on the clustering idea to study the air target grouping method under confrontation conditions, and transform the target grouping problem into a clustering problem for problem modeling and optimal solution. However, these methods all assume that the number of opponent target groups is fixed, Insufficient applicability of the method

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