Simplex Cubature Kalman-Consensus Filter for Distributed Space Target Tracking

Abstract EN

A simplex cubature Kalman-consensus filter, which is suitable for distributed space target tracking using multiple radars, is proposed to improve the target tracking accuracy.

The detailed orbital dynamics model and radar measurement model are given as the system filtering models.

The intractable nonlinear Gaussian weighted integral in the filter is decomposed into the spherical integral and radial integral, which are calculated using the spherical simplex rule and the second-order Gauss-Laguerre quadrature rule, respectively.

In this way, a new simplex cubature rule is derived.

By means of the statistical linear regression method, the posterior mean, covariance, and the transmitted messages in the extended Kalman-consensus filter are approximated using the deduced simplex cubature rule, which results in the proposed simplex cubature Kalman-consensus filter.

No data fusion center exists in the filter, and each radar only needs to exchange the information with its neighbors to reach a consensus estimate.

The simulation results show that the proposed filter can achieve more accurate results compared with the cubature Kalman-consensus filter.