Distributed hybrid consensus–based square-root cubature quadrature information filter and its application to maneuvering target tracking

To handle nonlinear filtering problems with networked sensors in a distributed manner, a novel distributed hybrid consensus–based square-root cubature quadrature information filter is proposed. The proposed hybrid consensus–based square-root cubature quadrature information filter exploits fifth-order spherical simplex-radial quadrature rule to tackle system nonlinearities and incorporates a novel measurement update strategy into the hybrid consensus filtering framework, which takes the predicted measurement error into account and hence produces more accurate estimates. In addition, the proposed hybrid consensus–based square-root cubature quadrature information filter inherits the complementary positive features of both consensus on information and consensus on measurements methods and avoids sensitive matrix operations such as square-root decompositions and inversion of covariances, which is beneficial for numerical stability. Stability analysis with respect to consensus, convergence, and consistency for the proposed hybrid consensus–based square-root cubature quadrature information filter is also developed. The effectiveness of the proposed hybrid consensus–based square-root cubature quadrature information filter is validated through a maneuvering target tracking scenario. The simulation results show that the proposed hybrid consensus–based square-root cubature quadrature information filter outperforms the existing algorithms at the expense of a slight increase in computational cost.