Aircraft Cluster Cooperative Positioning Method Based on Multi-Target Data Association

High-precision positioning of the aircraft cluster itself is a necessary condition for executing collaborative tasks. In scenarios where global navigation satellite systems are unavailable and environmental feature information is limited, a cooperative localization method based on multi-target data association has been proposed. A data link ranging polygon is constructed using the theory of indirect adjustment of the side measurement network. Similarity is calculated based on the topological characteristics of the target group, and targets are associated probabilistically. Subsequently, a least squares relative localization model is established based on the association results to enhance the cooperative localization accuracy of the aircraft clusters. Comparative experiments with different cooperative localization methods have been conducted. Simulation results demonstrate that the proposed method outperforms others in estimating the absolute direction of the ranging polygon in relative navigation, effectively suppressing the divergence trend of inertial navigation.