Research on Collaborative Location Theory for Cluster Based on Improved Weighted Centroid Algorithm
The acquisition of drone cluster positioning information is of great significance for path planning,detection,guidance,collaborative control,etc.Currently,the commonly used Global Navigation Satellite System(GNSS)positioning is easily affected by interference and deception and is in a denied state.The use of collaborative cooperative positioning based on inter-node data link is increasingly prominent.However,at present,there is still a lack of collaborative positioning algorithm that can achieve a good balance between positioning accuracy and computational burden.To solve this problem,the UAV cluster collaborative positioning method based on inter-node ranging is studied under GNSS denied environment.Firstly,a decentralized fusion positioning architecture for clustered UAV collaborative positioning is built.Then to address the issue of the inability to quantitatively evaluate the positioning performance of cluster drones under GNSS denied environment,a quantitative evaluation model for collaborative positioning accuracy of cluster is established and the UAV flight path and inter-node ranging information of each epoch under typical mission scenarios are constructed.Finally,through the simulation test,the relative position information of UAV cluster is obtained by using various algorithms including weighted centroid algorithm,least square method and grid method.The positioning performance of three positioning methods under the set typical scenario is evaluated.The problem of rapid divergence of positioning error of UAV cluster under GNSS denied environment is solved.Simulation results show that the weighted centroid algorithm has the highest cost performance.The research conclusions can provide some guidance and help for UAV cluster positioning.
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