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UAV-swarm cooperative situation perception consensus (SPC), a core part of swarm cooperative situation awareness (SA) consensus, directly influences whether a swarm could gain information superiority under complex mission environments. The related studies of evaluation indices and methods for UAV swarm cooperative SPC are not sufficient and are not very suitable for complex mission environments, e.g., battlefield or combat simulation environment, this paper systematically analyzes the connotation of swarm cooperative SPC, establishes the evaluation indices via information quality evaluation theory and proposes evaluation method of swarm cooperative SPC based on three-parameter interval number and Heronian mean (HM) operator. The proposed method includes developing a new method to represent multi-time evaluation indices by three-parameter interval number, proposing a variable weight strategy to obtain index weight and aggregating index information by three-parameter interval number weighted HM operator. The simulation results show that the established evaluation attributes can reasonably analyze the swarm cooperative SPC and the proposed approach can effectively deal with the uncertainty of situation information, the HM operator is superior to multiplicative synthesis in representing the correlations among attributes, compared to the evaluation method based on combined weights, the proposed approach has a better performance in the discrimination, which is more beneficial to the comparison of swarm cooperative SPC in different conditions.

UAV Swarm Cooperative Situation Perception Consensus Evaluation Method Based on Three-Parameter Interval Number and Heronian Mean Operator