Multi-missile Cooperative Navigation Algorithm Based on Adaptive SSUKF
In modern warfare,cooperative operation among missiles has become increasingly prevalent.To address the challenges faced by missiles in complex and harsh battlefield environments,where satellite navigation system functional-ity is severely constrained or even not positioning,leading to reduced accuracy in traditional SINS/GNSS integrated naviga-tion system,a multi-missile cooperative navigation algorithm based on adaptive SSUKF is proposed.Firstly,treating the SINS of each missile in the swarm as a reference,the relationships of relative position between the missiles within the swarm are obtained using data link measurements.Combining the information with the error equations of the SINS for each missile,a solution model for heterogeneous swarm cooperative navigation based on rank-deficient constraint serial filtering is estab-lished.Then,in response to the disadvantage of large computational complexity in UKF,the spherical simplex is employed instead of the traditional proportional symmetric sampling strategy.Leveraging the linear state equations of the model and the characteristics of additive noise,a simplified adaptive SSUKF algorithm for cooperative navigation is proposed.This al-gorithm significantly improves computational efficiency while ensuring accuracy.Lastly,simulation results show that the proposed algorithm effectively enhances the accuracy and adaptability of multi-missile navigation systems within heterogene-ous swarm networks operating in complex battlefield environments.The accuracy improvement is approximately twice that of pure SINS.Meanwhile,the computational efficiency is significantly enhanced compared to the traditional algorithms.
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