Abstract: In the cooperative hypersonic vehicle (HV) tracking problem,traditional nonlinear filtering algorithms may encounter numerical errors and collapse due to the accumulation of round-off errors when running on embedded systems with limited precision.To track HV more stable and faster,square root filtering was introduced in cubature rule-embedded information consensus filter (Cub-ICF),and the equivalent square root form was derived.This ensured the positive definiteness and symmetry of the covariance during the filtering process.On the basis of finite-time consensus algorithm,a finite-time consensus square root cubature information filter (FC-SRCIF) which combined the numerical robustness and convergence rate was designed.Simulation results demonstrate that FC-SRCIF outperforms existing cooperative tracking algorithms for both non-maneuvering and maneuvering targets.Particularly,for maneuvering target tracking,FC-SRCIF exhibits a 41.9% and 37.1% higher tracking accuracy in position and velocity compared to Cub-ICF,respectively,while also improving the convergence rate.These findings validate the unique advantages of FC-SRCIF in addressing the cooperative tracking problem of HV.

Key words: hypersonic vehicle, distributed state estimation, information filter, square-root filtering, finite-time consensus